TY - JOUR
T1 - A genetic algorithm with local search using activity list characteristics for solving resource-constrained project scheduling problem with multiple modes
AU - Okada, Ikutaro
AU - Takahashi, Koji
AU - Zhang, Wenqiang
AU - Zhang, Xiaofu
AU - Yang, Hongyu
AU - Fujimura, Shigeru
PY - 2014/3
Y1 - 2014/3
N2 - In this paper, we aim to solve the problem of resource-constrained project scheduling with multiple modes (rc-PSP/mM), in which multiple execution modes are available for each of the project's activity and with minimization of makespan as objective. We present a new genetic algorithm approach in order to solve this problem. In this procedure, we propose a new mutation operator that exploits a critical path and two new local search procedures, i.e. critical path improvement local search (cpiLS) and iterative forward/backward local search (ifbLS), using activity list characteristics. The cpiLS reduces the critical path and the ifbLS improves resource allocation of the schedule of rc-PSP/mM. Also, to evaluate the proposed approach, we compare the results of the computational experiment on certain standard project instances with the several competing heuristic procedures presented in the literature, and it has been revealed that our procedure is one of the most competitive among the algorithms.
AB - In this paper, we aim to solve the problem of resource-constrained project scheduling with multiple modes (rc-PSP/mM), in which multiple execution modes are available for each of the project's activity and with minimization of makespan as objective. We present a new genetic algorithm approach in order to solve this problem. In this procedure, we propose a new mutation operator that exploits a critical path and two new local search procedures, i.e. critical path improvement local search (cpiLS) and iterative forward/backward local search (ifbLS), using activity list characteristics. The cpiLS reduces the critical path and the ifbLS improves resource allocation of the schedule of rc-PSP/mM. Also, to evaluate the proposed approach, we compare the results of the computational experiment on certain standard project instances with the several competing heuristic procedures presented in the literature, and it has been revealed that our procedure is one of the most competitive among the algorithms.
KW - Critical path improvement local search
KW - Genetic algorithm
KW - Iterative forward/backward local search
KW - Precedence feasible activity list
KW - Reduction procedure
KW - Resource-constrained project scheduling problem with multiple modes
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U2 - 10.1002/tee.21955
DO - 10.1002/tee.21955
M3 - Article
AN - SCOPUS:84896832947
VL - 9
SP - 190
EP - 199
JO - IEEJ Transactions on Electrical and Electronic Engineering
JF - IEEJ Transactions on Electrical and Electronic Engineering
SN - 1931-4973
IS - 2
ER -