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Multiple objective immune wolf colony algorithm for solving time-cost-quality trade-off problem.

ABSTRACT: The importance of the time-cost-quality trade-off problem in construction projects has been widely recognized. Its goal is to minimize time and cost and maximize quality. In this paper, the bonus-penalty mechanism is introduced to improve the traditional time-cost model, and considering the nonlinear relationship between quality and time, a nonlinear time-cost quality model is established. Meanwhile, in order to better solve the time-cost-quality trade-off problem, a multi-objective immune wolf colony optimization algorithm has been proposed. The hybrid method combines the fast convergence of the wolf colony algorithm and the excellent diversity of the immune algorithm to improve the accuracy of the wolf colony search process. Finally, a railway construction project is taken as an example to prove the effectiveness of the method.

SUBMITTER: Liu G

PROVIDER: S-EPMC9910742 | biostudies-literature | 2023

REPOSITORIES: biostudies-literature

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Multiple objective immune wolf colony algorithm for solving time-cost-quality trade-off problem.

Liu Guanyi G Li Xuemei X Alam Khalid Mehmood KM

PloS one 20230209 2

The importance of the time-cost-quality trade-off problem in construction projects has been widely recognized. Its goal is to minimize time and cost and maximize quality. In this paper, the bonus-penalty mechanism is introduced to improve the traditional time-cost model, and considering the nonlinear relationship between quality and time, a nonlinear time-cost quality model is established. Meanwhile, in order to better solve the time-cost-quality trade-off problem, a multi-objective immune wolf ...[more]

PMID: 36757975

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