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Optimization time-cost-quality-work continuity in construction management using mutation-crossover slime mold algorithm
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DOI：10.1016/j.asoc.2023.110775.png)
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This study presents the mutation-crossover slime mold algorithm (MCSMA) to balance the time, cost, quality, and work continuity in a particular construction project. The slime mold algorithm is combined with the mutation-crossover method to modify the operating mechanism and increase the ability of finding optimal solutions in the exploration and exploitation space during the optimization process. The optimal exchange problem considers all the logical aspects of occurring activities and the obvious reasoning applied to choose a compromise solution in the project implementation. The MCSMA is compared with five well-known algorithms (i.e., OMOSOS, MOABC, MODE, MOPSO, and NSGA-II) to verify the effectiveness and performance of the proposed model. According to the analysis results, the MCSMA generates a diversification measure for both case studies with 0.501 and 0.485 C-Metric, 0.785 and 0.923 Spread, and 0.843 and 0.806 Hyper-volume. The algorithmic model represents development, improvement, and diversification in the problem of achieving model convergence and wide distribution and gives a better uniformity of optimal solutions compared to the other algorithms. (c) 2023 Elsevier B.V. All rights reserved.
Keyword:
Mutation-crossover slime mold algorithm
Time-cost-quality-work continuity
trade-off problem
Slime mold algorithm
Repetitive projects
期刊
IF:
6.6
论文数:
1.4W
被引数:
4.8W
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