A Review of Genetic Algorithm as a Decision-Making Optimization Tool in Project Management

9 pages•Published: May 15, 2022

Chinedu Okonkwo, Richard Garza, Tulio Sulbaran and Ibukun Awolusi

Abstract

Project Management requires a lot of decision-making, with chances of making a better decision increasing with an increase in available data. However, decision-making becomes increasingly difficult and complex as available data increases. The problem that this paper address is the lack of the ability of the rational human mind to process a large amount of data within a short period, thereby making poor decisions that could be influenced by lots of biases and reducing the chances of finding an optimal solution. This presents the need for optimization in decision-making with the aid of non- human intelligence/Artificial Intelligence. Therefore, the objective of this paper is to access the impact of Genetic Algorithms as a tool that can facilitate decision-making without sacrificing useful data that could optimize decision making. This study provides a review of genetic algorithms as an optimization tool for decision-making in project management. A comprehensive study is conducted on relevant literature from reputable journal databases. The study highlights the concept and benefits of genetic algorithm, followed by the drivers, as well as the barriers to its adoption. Findings from this paper will provide an insight into the research trend, level of adoption, and potential research areas in the use of genetic algorithms as a decision-making optimization tool. This study is expected to help project managers make a more informed decision in the adoption of decision-making optimization tools as using the right decision tool will free the human mind from mundane tasks to perform more creative tasks.

Keyphrases: big data, decision making, genetic algorithm, intelligent decision, project management

In: Tom Leathem, Wes Collins and Anthony Perrenoud (editors). ASC2022. 58th Annual Associated Schools of Construction International Conference, vol 3, pages 254-262.

Links:	https://easychair.org/publications/paper/4zTs
	https://doi.org/10.29007/jzcl

BibTeX entry

@inproceedings{ASC2022:Review_Genetic_Algorithm_as,
  author    = {Chinedu Okonkwo and Richard Garza and Tulio Sulbaran and Ibukun Awolusi},
  title     = {A Review of Genetic Algorithm as a Decision-Making Optimization Tool in Project Management},
  booktitle = {ASC2022. 58th Annual Associated Schools of Construction International Conference},
  editor    = {Tom Leathem and Wes Collins and Anthony Perrenoud},
  series    = {EPiC Series in Built Environment},
  volume    = {3},
  publisher = {EasyChair},
  bibsource = {EasyChair, https://easychair.org},
  issn      = {2632-881X},
  url       = {/publications/paper/4zTs},
  doi       = {10.29007/jzcl},
  pages     = {254-262},
  year      = {2022}}

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