ABSTRACT. With the increase in the use of the internet, freight transportation procurement websites have become an effective marketplace that brings together several carriers and shippers. These websites have made it possible for the shippers to transport goods more cheaply and safely. From the carriers’ point of view this situation has created the bid price determination problem in a fast procurement auction process. Carriers place bids in multiple auctions simultaneously and do not know the lanes they have won until the end of the auction due to the sealed-bid auction mechanism. This leads to uncertainty in the calculation of the lane bid price quotes at the beginning of the auction. Kuyzu et al. (2015) proposed a stochastic bid price optimization model for addressing the uncertainty in simultaneous procurement auctions. However, this model is a non-concave maximization problem requiring historical data and solving an exponential number of NP-Hard optimization problems. In real life, a high number of auctions may need to be priced at the same time. As a threshold matter of our method, we propose to follow a simpler approach so that the bid prices can be determined simultaneously and in a much faster manner. We develop an efficient synergy based method to calculate a full truckload carrier’s bid prices so that the carrier can compete with other carriers and win the tendered lanes in a profitable way. We show the effectiveness of the synergy based method through computational experiments involving a simulations of a virtual transportation procurement auction marketplace.

ABSTRACT. In the last decades, natural disasters have been affecting the human life of milions of people. The impressive scale of these disasters has pointed out the need for effective management of the relief supply operations. One of crucial issues in this context is the routing of vehicles carrying critical supplies and help to disaster victims. In such circumstances, selecting more reliable routes could help the rescue team to provide fast services to those in needs. In this paper, we focus specifically on the arrival time objective function in a multi vehicle routing problem where stochastic travel times are taken into account. The problem considered should be solved promptly in the aftermath of a disaster, hence we propose a fast heuristic that could be applied to solve the problem.

ABSTRACT. The donation-transplant network is a complex system which couples together standardized processes and high levels of urgency and uncertainty due to, respectively, organ deterioration over time and the unpredictability of time and location of organs eligible for transplantation activities. On the other hand, punctuality and reliability are key factors to ensure the safe outcome of the transplant. When a human organ is available for transplantation, it needs to be brought, in the shortest possible time, to the hospital where the patient is. Therefore, for long distances, transportation is often performed by air. In the work, an Integer Linear Programming (ILP) model to determine the optimal number and location of aircrafts in the given set of hubs is proposed, so as to satisfy all the given organ transportation requests. The objective is to minimize a weighted function of the number of aircrafts and the travelled distance. This problem falls in the category of uncapacitated facility location problems, if we consider aircrafts as facilities to be located in given hubs, and requests as customer demands. Two scenarios are tested and compared under the performance point of view and over different time windows extracted from the transplant database (single month, two months periods, three - four - six months periods and one year) to assess the influence of variation in demand pattern and time windows length on the number of aircrafts to be allocated to each hub. The cooperation with the Italian Transplantation Centre aims at investigating performance parameters, and at proposing solutions to enhance efficiency and reliability of organ transport network while optimizing costs. This is a standalone action within Europe to support strategic policies as transplant activities are.

ABSTRACT. Introduction Development of information technologies over past years has provided a high level of informatization and virtualization of technological processes at contemporary transport markets. This led to the changes in a role of freight forwarders as of companies providing intermediary services. Contemporary forwarders are the architects of supply chains that provide the most efficient way of interaction between the transport market participants. Therefore, the efficiency of the forwarding companies technological processes nowadays is one of the key factors which determines an efficiency of freight transport systems. The demand model is an essential element in any decision support model in the field of transport and logistics. The adequacy of the applied demand model and the data used in order to develop it assure correct simulation results of logistics systems. Modeling of demand for forwarding services is a particularly complex problem due to a large number of stochastic factors forming demand and limited access to sources of up-to-date demand parameters. Aim of paper The paper goal is to present an approach to simulations of demand for freight forwarding services which considers stochasticity of demand on the grounds of the requests flow model. The proposed approach is described with the use of the mathematical model and respective software implementing the model. Methodology The literature analysis (Allen, Albert and Schaefer, Barone et al., Chow et al.) suggests that the task of estimating demand for freight deliveries is usually considered as a numerical evaluation of a single parameter used to characterize demand. In most of the existing approaches, the estimation of demand parameters is based on the determination of their predicted values. Typically, the predicted value of a parameter is determined on the basis of statistical data for previous periods of time, which makes it much more difficult to investigate the processes of demand-shaping. Such an approach yields incorrect estimates of the demand parameters. We propose to describe demand for cargo deliveries on the basis of a model of the requests flow, which generates respective informational, material and financial flows in the macro-logistics system of the transport services’ market (Naumov and Kholeva). Such an abstraction corresponds to the actually used principles of communication between the transportation market entities: the process of freight owners and carriers’ servicing is performed by freight forwarders with the help of informational logistics portals. At the modern markets of the road freight transportation, ensuring the needs of freight owners for cargo deliveries and the needs of carriers for vehicles loading in most cases is provided under the mediation of a freight forwarding company as an operator servicing the flow of information about clients’ requests. The basic unit in the demand model, is a request for transportation services – a need of a client for services, supported by its purchasing abilities and presented at the market in order to be satisfied. A set of potential and actual requests for the company’s services forms a demand for its services; respectively, a set of requests for services of all companies in a region represents the demand for transportation services in this region, etc. Each request could be quantified by a set of indicators, the most significant of which are the shipment volume, the delivery distance and time interval between requests. Since a set of consecutive requests for services of transport companies characterizes the demand, the demand estimation problem could be transformed into the problem of the request flow parameters estimation. An information about the requests flows for the particular forwarding company could be obtained on the base of data from this company, and for the transportation market as a whole – on the base of data from specialized information portals. The convenient way to present geographical characteristics of requests while modeling the demand for transport services is to combine them in the origin-destination matrix (O-D matrix) mapping requests distribution according to delivery directions. So, it’s not enough to determine numerical parameters of the demand in order to characterize it. Additionally, the O-D matrix should be defined to describe a demand for freight forwarding services in the region. Results In the paper, we briefly present results of studies of the demand parameters for freight forwarding services in Poland provided on the grounds of data from the trans.eu logistics portal: O-D matrix for the regions of Poland, the demand structure and distributions of the numerical demand parameters were obtained. In order obtain data samples and to model demand for freight forwarding services, we developed the appropriate simulation procedures using the Python programming language. The paper describes basic algorithms of the proposed procedures and approaches to the demand modelling on the base of these procedures. The paper introduces some numeric results of the demand simulations with the use of the developed software. An adequacy of the proposed approach to the demand modeling is justified by the example of simulations of the demand for freight forwarding services in Poland. The quality of the results of numerical modeling of demand parameters as random variables is proposed to check on the basis of the Pearson chi-square test. Initially, the empirical frequency vector is set for the empirical values, and for a sample of the parameter values generated by the model the theoretical frequency vector is estimated; on the basis of these vectors, the chi-squared test statistic is calculated. For all random variables in each model implementation, it was found that the hypotheses about the convergence of empirical and theoretical distributions were not rejected. The fit of the O-D matrix was evaluated on the basis of the determination coefficient. The coefficient value is calculated from the empirical variance of the matrix and the variance of the error – the difference between the corresponding element of the empirical indicator and the theoretical value obtained in the model implementation. Estimations of the determination coefficient for the OD-matrices of the simulated demand have demonstrated the high accuracy of the demand models obtained with the use of the developed software. Originality The developed method allows researchers and forwarding managers to consider stochastic nature of demand for cargo deliveries. The proposed software to modeling of demand for forwarding services is a tool for estimations of numerical parameters of the requests flow as random variables, which also considers the distribution of demand with respect to geographic regions. As an opposite of other existing approaches, the proposed method uses publicly available information as input data for demand modeling. Conclusions Described numerical parameters for demand assessments are the main characteristics on which base the model of demand for forwarding services should be implemented. However, the proposed model could be widened, and other demand characteristics could be considered. The developed class library for modeling interactions between freight market operators is an effective tool for modeling demand for freight forwarding services, as evidenced by the results of the simulation experiment. The demand model based on the presented approach could be used as a subsystem of other more sophisticated simulation models to solve a number of problems in the area of freight forwarding, for example: defining the strategy for freight market participants, developing effective variants of the customer service processes, improving the vehicles fleet structure, etc. References Albert, A., Schaefer, A.: Demand for freight transportation in the U.S.: A high-level view, 54th Annual Transportation Research Forum 2013, p. 103–120. Allen W.B.: The demand for freight transportation: A micro approach, Transportation Research 1977, vol. 11/1, p. 9–14. Barone, V., Crocco, F., Mongelli, D.W.E.: Freight transport demand models for applications in urban areas, Applied Mechanics and Materials 2014, vol. 442, p. 634–644. Chow J., Yang C.H., Regan A.C.: State-of-the art of freight forecast modeling: lessons learned and the road ahead, Transportation 2010, vol. 37, p. 1011–1030. Naumov V., Kholeva O.: Studying demand for freight forwarding services in Ukraine on the base of logistics portals data. Procedia Engineering 2017, vol. 187, p. 317–323.

ABSTRACT. 1. Background and literatures In recent years, a growing number of researchers have focused on the concept of synchromodal transportation. SteadieSeifi et al. (2014) mentioned that synchromodality is the next step after intermodal and co-modal transportation. As proposed by the Dutch institute for advanced logistic (dinalog), synchronmodal transport entails that a shipper agrees with a service operator on the delivery of products at specified costs, quality, and sustainability but gives the service operator the freedom to decide on how to deliver according to these specifications. (dinalog, 2015). Most studies on synchromodal are from strategic level. B. Riessen et al. (2015) overviewed relevant researches around three topics related to the case of European Gateway Services, the network orchestrator of container transportation network in the Rotterdam hinterland. For each topic they described studies with practical relevance results. Until that time, there exist no exact models and quantitative analysis of synchromodal and other multimodal transportation from operation level. M. Zhang, A.J. Pel (2016) first compare the intermodal and synchromodal operations from economic, societal and environmental perspective. The model includes three parts: (1) a demand generator, which generate relevant day to day and within day dynamics in freight transport demand; (2) infrastructure & service network processor, which stretch a time dependent supply capacity of a multi-modes network; (3) the schedule based assignment module, which operates at path level allocating the modes, terminals, service lines and departure time. a case study based on the port of Rotterdam shows that synchromodality system is likely to improve the service level, capacity utilization, and modal shift. Still, the delivery cost is not reduced. L. Li et. al., (2017) investigated a distributed model predictive flow control (DMPFC) for synchromodal transportation. They introduced interconnecting variables and interconnecting constraints among the planning problems of each of the operators. They solve the DMPFC problem with three distributed model predictive flow control approaches: the parallel and serial augmented lagrangian relaxation, and the alternating direction method of multipliers. From the literature studies, we find that most of the few researches are mainly form conceptual and policy point. There are very limited researchers into its modelling and analysis. We build a time-space network model, to assess the expected flexibility and efficiency impacts, at operational level. 2. Mathematical model The model orchestrates container transportation throughout the network, based on the following assumption: 1) Containers are the transportation unit. Form the origins or destinations, the loading units will not change. 2) More than one transportation mode is involved. Here we refer to trucks, trains and barges. 3) One dispatch centre is responsible for all operation decisions based on the update information of available vehicles from all modes. The customers have requirements about the delivery time. However they will not be involved in the transportation modes choice and transhipment. The model is based on a space time network, allocates the transportation identities to available modes, and agilely reacting to the dynamics in the freight transport process. The problem is formulated as a single-objective mixed-integer programming problem, where the objective is to minimize the total cost, based on on-time delivery expectations. The cost includes: fixed cost of using vehicles, transportation cost according to the distance, the transhipment cost and penalty cost due to late or early deliveries. Integer variables are used to decide the amount of containers allocated to each transportation mode via all the arcs. Continuous variables are used to follow the departure or arrival time of the containers. The constraints can be generalized into three categories: Flow constraints. The difference of incoming containers and outgoing containers at each node (supply, transhipment, demand) satisfies its demand of corresponding identities； Available resources constraints. The allocated number of containers are within the available total capacity of the total vehicles. Meanwhile, the movement of vehicles lead to a dynamic capacity of the network； Time constraints. 3. Results/Findings This model emphasizes the real-time flexibility and optimizes the use of available resources. Decisions about mode choice, route choice, flow allocation, and departure times, are given flexibly according to the real time situation. This postponement of decisions is the main difference compared with intermodal transportations. For example, alignment is achieved through flexible vehicle departure time and full information of the arrival time of containers en route. Finding the optimal plan becomes more difficult when we add more real-world assumptions in forms of constraints. The model is built to capture almost all possibilities during the transportation process to achieve this flexibility. The problem is large and NP hard. We expect to achieve a solution within acceptable solution time with a suitable heuristic. This is an ongoing research. The above described model above will be tested with real data from the Port of Rotterdam, expected around March. 2018. We expect that a Synchromodal network brings more benefits in terms of time, money, and reliability when comparing to a traditional transportation network. 4. Implications for Research Synchromodal transportation is positioned as the next step after intermodal and co-modal transportation. It promises increased flexibility and robustness at lower costs. Our model involves a structured, efficient and synchronized utilization of available transportation modes. Meanwhile, it will boost sustainable transportation in the long run. Since the model focuses on shifting containers from trucks towards barges or rail, decreased emission of CO2 can also be expected. Currently, we have not yet studied the effect of real-time decision support in case of disturbances or disruptions. Future researches can also explore the robustness of the network at the tactical level. References van Riessen B., Negenborn R.R., Dekker R.， 2015, Synchromodal Container Transportation: An Overview of Current Topics and Research Opportunities. In: Corman F., Voß S., Negenborn R. (eds) Computational Logistics. ICCL 2015. Lecture Notes in Computer Science, vol 9335, pp 386-397. Springer, Cham SteadieSeifi, M., Dellaert, N.P., Nuijten, W., Van Woensel, T., Raoufi, R., 2014. Multimodal freight transportation planning: a literature review. Eur. J. Oper. Res. 233, 1-15. Dinalog, 2015. Synchromodal transport. Zhang, M. and Pel, A. J. 2016, “Synchromodal hinterland freight transport: Model study for the port of Rotterdam”, Journal of Transport Geography, Vol. 52 No. 1, pp. 1-10. Li, L.; Negenborn, R.R.; De Schutter, B. 2017. Distributed model predictive control for cooperative synchromodal freight transport. Transp. Res. Part E, Vol. 105, pp. 240-260.

ABSTRACT. Aim, scope and literature review Surface transportation, including road transportation, is a dominant transportation mode for moving goods/ freight world-wide. According to [12] up to 60% of all transportation is done on surface. Freight road movements play a critical role (next to warehousing) in various logistic networks. Many recent research projects have been carried out and many reports have been published in the area of road freight transportation [2, 9, 12, 13, 14, 15].

Traditional models of freight transportation optimization were single-objective formulations, focused on cost minimization [3, 4]. More recently, different authors have proposed more realistic and comprehensive approaches for handling freight transportation problems, including multiple criteria formulations.

Work [1] contains a formulation and a solution procedure for a multiple criteria, multimodal transportation problem focused on efficient changes of transportation modes. In [9] authors formulate a multiple criteria ranking problem to evaluate freight transportation quality and use the Analytic Hierarchy Process (AHP) to rank alternative criteria. Several papers [2, 10, 11, 13] refer to green freight road transportation and demonstrate multiple criteria formulations for handling transportation processes. One of the examples is paper [10] where the authors consider several criteria (including the environmental-oriented ones), such as: cost, noise, pollution and fuel consumption while solving a vehicle routing problem. They propose a solution procedure that features the balancing and trade-off analysis of the abovementioned criteria, and they conclude that the application of multicriteria optimization methods makes it possible to slightly control and limit the carbon emissions. This is a follow-up of an earlier paper [11] where a green version of the combined traveling salesman and transportation problems was considered. Finally, in [2] authors review recent papers which give priority to such formulations where the optimization focuses on limiting emissions of harmful substances, such as CO2 into the atmosphere.

Some of the many other problems tackled in the field include those in papers [14, 15]. In [14] authors solve a multicriteria fleet sizing problem for road freight transportation, while in [15] transportation performance for selected companies is analyzed with multicriteria evaluation in mind.

This paper further extends the area of multiple criteria oriented road freight transportation research and presents the formulation and a solution procedure for a multiple criteria problem of vehicle routing joined with a ranking generation problem. The approach focuses on obtaining a hierarchy of transportation tasks for a private truck fleet owner (or a driver, in case of single-driver companies) based on their preferences as well as the preferences of the task providers. On one hand, to obtain the hierarchy it is necessary to solve a multicriteria extension of the vehicle routing problem. On the other hand, to solve the vehicle routing problem, a ranking is required. This leads to a complex and interconnected optimization problem that is difficult to solve.

Although the problem of strategic management in transportation systems is not novel [8], currently there is a growing number of papers that indicate the need to incorporate preferences of the drivers into the decision making processes [5, 6, 7]. Authors of [5] consider a multicriteria routing problem that mixes driver preferences with travel time and travel safety as a main criteria, while authors of [6] model the driver behavior using analytic hierarchy process. Finally, authors of [7] consider driver preferences regarding paid managed lanes.

The authors of this paper include preferences of the driver in the decision making problem, leading to novel, specific criteria and constraints as explained in the following section. Methodology We formulate a decision making problem consisting of two main interconnected partial problems. Given a driver and a set of transportation tasks, the fundamental goal considered in the paper is the generation of a hierarchy of tasks to be assigned to the driver. Tasks are ranked according to drivers’ preferences and task properties. Secondary goal is to design a route that ensures the execution of all the delivery tasks. Driver is described by a set of properties as well as expectations towards the transportation tasks they are willing to undertake. Tasks are defined by a set of properties and requirements. In general, we assume that the driver already has a route. This includes a starting and an ending point as well as starting time and an ending time. It is therefore necessary to evaluate the tasks according to how well they merge with the tasks already assigned. The addition of a new task changes the parameters of the route. New route is computed and evaluated according to a complex quality measure. The quality measure consists of multiple individual criteria such as: profit for transfer, cost of transfer, safety of transfer, dwelling times, comfort of transfer, timeliness, driver preference and driver aptitude. Profit is the payout for finishing the transportation tasks. Cost of transfer is the financial spending necessary to follow the given route. This includes fuel cost, handling and tolls. Safety is the aggregated (over the route) measure of active and passive elements such as safety characteristics of the vehicle, of the driver and safety along the route. Dwelling times are the stops along the route that extend the total traveling time. Comfort of transfer is the overall convenience of picking the route. Comfort can be decreased by selecting low quality roads and increased by picking route fragments favored by the driver. Driver preference is the aggregated preference towards all the undertaken transportation tasks. Driver aptitude is the expectation of the driver to be successful in coming to an agreement with the task provider. This is calculated by comparing the requirements set by the task provider with properties of the driver. The solution, which is the hierarchy of tasks and the selection of corresponding routes, is subject to various constraints which limit the feasible set. Constraints are divided up into three groups: regarding routes, regarding driver preferences and regarding driver aptitude. First type of the constraints is always present. We permit a situation in which some of the two latter constraint types are inactive, i.e. the driver or the task provider has no preference. Route constraints ensure that the route is made up of correctly interconnected stages, that it starts in the given starting point and that it ends in the given ending point. They also ensure that pickup takes place before delivery and that all pickups and deliveries are on the route. Preference constraints ensure that minimal safety and comfort constraints are met, that maximal dwelling times are not exceeded and that the profit to cost difference is within acceptable bounds. Furthermore, the constraints guarantee that every task is acceptable from the driver's viewpoint. Aptitude constraints ensure that the driver can perform every task. That includes that the volume of the package is within acceptable bounds, that the driver is sufficiently experienced to handle the task and that the truck is equipped with all the necessary appliances, such as a freezer which is typically needed for food transportation. The problem described is formulated as a constrained multicriteria optimization problem. We show that it is hard to solve in reasonable time so that a solution algorithm has to focus on finding feasible solutions first. We provide a dedicated algorithm described in the following section. Results and conclusions We propose and evaluate a dedicated decision making procedure that, for a given driver and a set of tasks, generates a hierarchy of tasks according to driver preferences and task properties. This is obtained through decomposition of the original, complex problem into a series of iteratively solved partial problems of hierarchy generation and vehicle routing. We show that the problem is hard to solve in reasonable time, therefore a heuristic approach is necessary. We provide such a method and evaluate it through empirical simulations. We compare instances with drivers of varying preferences, we evaluate solutions for transportation networks of different sizes and we simulate cases with varying number of homogeneous and heterogeneous transportation tasks. We show that the proposed method is capable of quickly solving real-life sized instances. References [1] Dib O, Manier M, Moalic L, Advance Modeling Approach for Computing Multicriteria Shortest Paths in Multimodal Transportation Networks, 2016 IEEE Int. Conf. on Intelligent Transportation Engineering, pp. 40-44, (2016) [2] Demir E, Bektas T, Laporte G, A review of recent research on green road freight transportation, European Journal of Operational Research 237, pp. 775-793 (2014) [3] Crainic T, Service network design in freight transportation, European Journal of Operational Research, 122(2), pp. 272–288 (2000) [4] Forkenbrock D, Comparison of external costs of rail and truck freight transportation. Transportation Research Part A: Policy and Practice, 35(4), pp. 321–337 (2001) [5] Bozkurt A, Yazici A, Keskin K, A Multicriteria Route Planning Approach Considering Driver Preferences, 2012 IEEE Int. Conf. on Vehicular Electronics and Safety, July, Instanbul, Turkey, pp. 324-328 (2012) [6] Sun Y, Wu Y, Sun Z, Optimal route selection method based on grey incidence analysis, IEEE Int. Conf. on Automation and Logistics, 1-6, pp. 2495-2499 (2007) [7] Cherry C, Adelakun A, Truck driver perceptions and preferences: Congestion and conflict, managed lanes and tolls, Transport Policy 24, pp. 1-9 (2012) [8] Bander J, Nagarajan A, White C, Strategic management of intelligent transportation systems: the case of freight mobility systems in the trucking industry, IEEE Int. Conf. on Systems, Man, and Cybernetics (1998) [9] L'och M, Dolinayova A, Evaluation Quality the freight Transport through Application of Methods multi-criteria Decision, Procedia Economics and Finance 32, pp. 210-216 (2015) [10] Sawik B, Faulin J, Perez-Bernebeu E, A Multicriteria Analysis for the Green VRP: A Case Discussion for the Distribution Problem of a Spanish Retailer, Transportation Research Procedia 22, pp. 305-313 (2017) [11] Sawik B, Faulin J, Pérez-Bernabeu E, Multi-Objective Traveling Salesman and Transportation Problems with Environmental Aspects, Applications of Management Science 18 (eds. Lawrence K, Kleinman G), Bingley UK: Emerald Group Publishing Limited, pp. 21-55 (2017) [12] Alam A, et al, Heavy-Duty Vehicle Platooning for Sustainable Freight Transportation, IEEE Control Systems Magazine 35/6, pp. 34-56 (2015) [13] Jabir E, Panicker V., Sridharan R, Multi-objective optimization model for a green vehicle routing problem, Procedia – Social and Behavioral Sciences 189, pp. 33-39 (2015) [14] Żak J, Redmer A, Sawicki P, Multiple objective optimization of the fleet sizing problem for road freight transportation, Journal of Advanced Transportation 42, pp. 379-427 (2011) [15] Baran J, Żak J, Multiple Criteria Evaluation of transportation performance for selected agribusiness companies, Procedia - Social and Behavioral Sciences 111, pp. 320-329 (2013)

ABSTRACT. The e-commerce is a sector in continuous growth in all countries and, in particular, the growth of B2C (Business to Consumer) e-commerce market has an important impact on last mile deliveries in the city area. A delivery of a parcel to consumers’ address has high costs both for courier (extended car route) and for consumers (high price) and also for the greater environmental pollutions. The growing demand for deliveries in the urban area involves an increase of traffic and congestion problems and, consequently, environmental issues. In recent years many studies are focused on alternatives measures which could reduce negative aspects and impacts of the last mile delivery. Good practices to rationalize the last mile delivery should be the use of different systems such as reception boxes, delivery boxes, controlled access systems, collection points and lockers. This paper aims to compare two different alternative options to home delivery. In particular, we propose a comparison between point-to-point and lockers, pro and cons both of them and define the best positions where located lockers to reduce the consumers’ deviations. The proposed methodology has been applied to a real case: the Italian municipality of Dolo.

ABSTRACT. We present a tool to support the operations manager of small trucking companies. The tool integrates modules to manage pickup/delivery requests, determine initial assignment to trucks and service routes, react to dynamic events, support demand forecasting. Modules are interconnected by a cloud platform and take advantage from real-time data sharing. The core of the tool is a neighborhood search heuristic for a Vehicle Routing Problem with side attributes, to be solved in both static and dynamic settings. The efficiency of the algorithm is improved by neighbor filtering and parallel implementation. A prototype implementation of the tool currently supports the operations at Trans-cel, a small freight transportation company. Tests on the field on different operational scenarios show that the algorithm fits both static and dynamic settings in terms of running times and quality of the suggested solutions.

ABSTRACT. Cargo Transportation management should be focused on the preparation and implementation of credible plans for goods delivery from suppliers to consumers. Transportation schedules are often violated due to objective reasons. Effective functioning of the technological process of cargo transportation is impossible without taking into account the human factor. An important element of the technological process, which has a significant impact on the efficiency of the entire process, is the choice of time norms for the execution of technological operations. These technological operations are performed with the participation of the driver and the timeliness of this performance depends on him. Due to this, the optimal technological parameters of cargo transportation can be evaluated considering the driver's state. The research is aimed at assessing the change in the transportation speed on the route of considering the driver's state. The transportation speed is described as a function of the factors characterizing the truck, transportation technology, traffic conditions for truck and drivers. The driver's state is assessed based on the analysis of the change in their cardiogram when performing the elements of the transportation process. Assessed the influence of each considering factor on the transportation speed, it is possible to evaluate the parameters of the transportation technology, which are optimal from schedules limitation point of view. The results of the conducted research allow identifying the model of the change in the service speed on the routes considering the driver's state, which can be used for designing the overall parameters of the technological process of cargo transportation.

ABSTRACT. The paper is devoted to such topical problem as the organization of spare parts delivery taking into account ecological risks. Existing possibilities to increase the ecological compatibility of transportation are analyzed. Possible ways to improve the delivery of spare parts from the manufacturer to the dealer centers and warehouses are considered. The automobile corporation PC “KAMAZ” has been selected as the unit of analysis because it has a wide network of dealers and warehouses both inside the country and abroad. Authors have determined points of delivery, for which more environmentally friendly routes taking into account the peculiarities of the Russian transport system can be developed. When transiting to a circular economy, the tasks of organizing the remanufacturing of faulty spare parts have to be solved, in particular, the organization of their reverse delivery to the manufacturer. This causes additional requirements when building the supply chains. The algorithm for organizing the delivery of faulty spare parts from large warehouses to the manufacturer by vehicles’ return trips, which helps to minimize empty runs, is proposed.

ABSTRACT. The purpose of this research is to introduce an analysis, qualitative and whenever possible quantitative, on how Cooperative Intelligent Transport Systems (C-ITS) can affect a Supply-Chain Logistics System. The considerations deepens the role and the importance that Logistics covers within a company, its cost structure and the evolution it crossed from a Physical Distribution Management to a Supply-Chain Management. Its increased importance, requires a more sophisticated applications in order to optimize its costs, as well as in order to find new opportunities of developments, applications which requires a careful evaluation method in order to assess their effective adoption. The research is based on a literature review on the most important European Road ITS projects evaluation methods and classifications of the main C-ITS categories and benefits. The result of the investigation is a classification impact analysis of C-ITS providing different kind if benefits to the Logistics cost structure of a company. In addition to this, there depicted possible future scenarios which can redesign the Distribution Network, changing also the perspective within the role of the actors involved in the Supply Chain.

ABSTRACT. Note: Please find extended abstract attached

Innovative transportation technologies, like the Hyperloop concept and a new generation of drones and zeppelins, promise solutions for modern cargo transport. The integration of innovative transport systems into existing transport networks presents a challenge not only from a technological point of view, but also has unknown economic, social, and ecological impacts. Therefore, this work aims to answer the following research question: How to estimate the regional impact of a connection utilizing innovative means of transport? A scalable method is presented, which is not limited to a specific type or limited number of regions, but capable to estimate the impacts of large-scale transport networks, which cover a great number of diverse regions. The work contributes to quantitative transport network modelling, as it provides a method for the quantification of essential regional impacts, which can be incorporated into comprehensive transport network models. The applicability of the method is demonstrated with a real-life example. As a result, values of an impact indicator for international regions with particular relevance to Austria are available for the Hyperloop, cargo zeppelin, and Cargo Sous Terrain, as well as combinations with cargo drones.

ABSTRACT. Aim of paper and literature review

Growing competition at the European market and the strong need for companies’ adjustments to rapid changes in the economy requires that the delivery process of materials and components to manufacturing plants must be efficient, smooth and reliable. Enterprises strive for minimizing manufacturing costs of their products (finished goods, components) and put enormous efforts on shortening the duration of the flow of goods delivered to the customers to satisfy their expectations concerning quick delivery. At the same time they try to generate the maximum value of goods and services to build customers’ satisfaction and loyalty. The concept of global sourcing [5] and the cooperation with the suppliers, who operate in developing countries, is one of the strategies to decrease manufacturing costs. That is the reason why more and more products offered at the European and United States markets come from China. China is the market which performs a vital role taking into account the migration of manufacturing to the developing countries (especially, keeping in mind those countries where the labor costs are lower). China, for the last thirty years, has recorded constant economic growth – on the average 10%. Such results are unprecedented in any other economy [1]. Besides, the forecasts present further development and economic growth of China caused by increasing trade activity between Asian and Pacific countries (the United States in particular) and number of investments in China and India. Still, the trade between the United States and the European Union will be the most important but the biggest growth in that respect will be designated to the trade with Asia [9]. China would be able to approximate or even catch up with the United States in the following decades according to the forecasts [1]. That is why China is the very interesting supply region which advantages are used more and more often by European (including Polish) manufacturers. However, there are certain trade-offs with the Chinese market. Decreased manufacturing costs, achieved by relocation of production to China, may lead not only to the increase in the transportation and storage costs but also to the extension of delivery time [8]. These are the main purposes for dynamic development of the advanced supply chain solutions and novel freight transportation concepts, proposed in the recent years. Freight transportation is the set of activities connected with relocation of shipments in time and space with proper means [3,5]. It is covering a distance or a change of place of goods using the transport facilities [10]. The general definition of the transportation defines it as a process which is the finite sequence of activities necessary to relocate shipments [2]. Its efficiency is determined by delivery of goods on time, to the right place, consistent with the decision of a person who assigns a transport service [6]. The set of transportation processes creates the transportation system. In this paper, the global freight transportation system is the main focus. It is defined as a set of components, such as: transportation infrastructure, fleet of vehicles, human resources and governing rules that ensure a coordinated and efficient transfer goods from their origins to destinations in a certain area [16]. The system has huge influence on functioning the international trade exchange where costs and time of transportation are very important [7]. Part of the transportation system are transportation solutions/ corridors, i.e. concepts of moving goods between supply chain links on a described scale with the application of a single-mode, multi-modal, inter-continental, world-wide transportation. The transportation solutions must fit the local or global configuration of manufacturing and distribution systems and strategies to provide the desired customer service at the lowest possible cost and to maximize the supply chain profit [15]. In this paper, taking into account the transportation China-Europe (especially Poland), the global transportation sollutions, with the multi-modal transportation, were designed end evaluated.

The overall research goal of this paper is to develop a universal, generic methodology of designing and evaluating the global freight transportation solutions. The authors of this paper claim that this aspect has a multiple criteria character, and thus develop the proposed approach based on the principles of Multiple Criteria Decision Making/ Aiding. The challenge and the novelty of this work is to present the design of the alternative options – freight transportation corridors, the comparison of the multiple criteria evaluations of them and selection of the most desirable one. The proposed methodology will involve a complex, global transport corridors, where many different aspects (eg. delivery cost, delivery time) should be taken into account.

Methodology

The proposed approach based on the Multiple Criteria Decision Making/Aiding (MCDM/A) Methodology. It is a field of study that develops rules, tools and methods supporting the decision maker (DM) in solving complex decision problems, in which several – often contradictory – points of view must be taken into account [4,13,17,18]. According to B. Roy [11,12] Multiple Criteria Decision Making/Aiding is the activity of an analyst who helps to a DM, during a decision making process, to find answers for questions asked to find the most desired solutions, taking into consideration multiple aims (criteria) which are formulated by the DM. The methodology of MCDM/A has a universal character and can be applied in various cases when a DM solves a so called multiple criteria decision problem (MCDP). MCDM/A simplifies the process of carrying out most of the stages of the decision process, starting from formulation of decision aims, through creation of options and finally choosing the best of them [14]. In the proposed approach the authors have distinguished two major steps: 1. The design of freight transportation corridors. 2. The evaluation of the alternative options and selection of the most desired solution. In the design phase the authors propose a heuristic approach supported by a series of simulation experiments. The goal of this step is to define different freight transportation solutions. The authors apply in this phase brain-storming techniques and expert system to develop several transportation corridors. In this phase they puzzle with different components of the transportation infrastructure, match alternative transportation modes and transportation ways. They simulate the behavior of the developed transportation solutions and generate their characteristics, such as Cost of Transport, Delivery Time, Timeliness, Reliability, Flexibility and Safety of Delivery (Transportation) and Comfort for the Customer. For the simulation process they use commercial spread sheets, such as Excel. As a result authors describe six multi-modal transportation corridors, in which were used components such as: waterway, railway, road and airway. An example of a proposed solution is the variant- global transportation corridor, in which are four stages: sea transport from port in Qingdao (China) to Hamburg (Germany) port, sea transport from Hamburg to Gdynia port, rail transport from Gdynia to container terminal in Strykow (Poland) and road transport from Strykow to company's central warehouse (Lodz). The generated parameters are used in the evaluation phase. In the evaluation phase the decision problem is defined as a multiple criteria ranking problem. Considered variants represent international transportation corridors and correspond to different multi-modal transportation solutions that allow to transfer textile goods from China to the medium-sized company operating in a garment/ clothing industry. The company has its headquarter in central part of Poland- Lodz. The produced and transported assortments are clothes, shoes and accessories, for a wide range of customers of all ages. Searching for the global sourcing solutions and focusing on the reduction of the manufacturing/ logistics costs the company decided to relocate its manufacturing processes in China, based on the outsourcing principles. Then they target to the company's central warehouse (Lodz). The considered variants are evaluated by a set / family of criteria (multi-dimensional analysis). The evaluation phase covers such steps as: definition of a consistent family of criteria that allows for a comprehensive evaluation of the generated variants (transportation corridors), modeling of the decision maker’s (DM’s) preferences (including: the definition of the importance of criteria and the DM’s sensitivity towards changes of criteria values), computational experiments resulting in the final ranking of freight transportation systems and finally the selection of the most desired one. Computational experiments are carried out with the application of selected MCDM/A methods, such as Electre III/IV and AHP.

Results and conclusions

The ranking of the variants (transportation solutions) has been performed with the application of different programs, which are the implementation of Electre III/IV and AHP methods. In accordance with the algorithm of the applied methods, the evaluation matrix of each variants (V1, V2, ...V6) of global transportation corridors has been constructed. Then next steps were followed, according to the algorithms of both methods. As a result of computational experiments, final rankings were obtained. Rankings resulting from the application of both methods showed that the best variants are two transportation corridors. They are both variants characterized by a lot of values, even though they do not provide the lowest cost of transportation. The paper has both methodological and utilitarian character. It indicates the way of analysis and assessment of global transportation solutions in order to rank corridors from the best to the worst, in compliance with the multiple criteria methodology. The methodological approach is based on the presentation of multiple criteria decision making procedure (ranking of the variants) in order to enable the optimum selection of global transportation solutions. In practical terms the authors demonstrate the best variants- transportation solutions which can be used by the described company.

References

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ABSTRACT. More recent studies stress the importance of the role of freight activities location for urban freight movement as land-use factors have important influences on freight activity in urban areas. Although the location of shops, warehouses and distribution centres has impacts on freight distribution mobility and shopping mobility, according to their distance from urban centres, little attention has been paid by local administrators to urban land-use governance able to govern shopkeepers’ location choices. Several reasons, e.g. the implementation of long-term city logistics measures or the threat of commercial rent increasing, can have high impacts on moving business from city centre to surroundings. Therefore, it becomes critical for city planners to have tools for assessing the effects of such a choice. Models able to simulate the shopkeepers’ behavior in location choice can then be useful for who wishing to anticipate and plan necessary actions for mitigating the externalities of urban freight transport. This paper move from the statement that the shopkeepers’ choices are mainly influenced by the forecasting of customers’ choice. Then, it presents a first part of a before-and-after analysis of the shopping trips behaviours in the context of an actual store movement from the city center of Saint-Etienne. Starting from some surveys carried-out before the movement, it proposes a decision-tree analysis to identify the major factors influencing customers’ choice in remaining store- customers or not after such a movement. Over the peculiarities of the store and the city, the tree structured model underpins many findings available in the general literature about shopping trips.