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• W2079264914 abstract "Resource-constrained project scheduling problem (RCPSP) is a very important optimization problem in construction project management. Despite the importance of the RCPSP in project scheduling and management, commercial project management software provides very limited capabilities for the RCPSP. In this paper, a hybrid strategy based on genetic algorithms, and simulated annealing is presented for the RCPSP. The strategy aims to integrate parallel search ability of genetic algorithms with fine tuning capabilities of the simulated annealing technique to achieve an efficient algorithm for the RCPSP. The proposed strategy was tested using benchmark test problems and best solutions of the state-of-the-art algorithms. A sole genetic algorithm, and seven heuristics of project management software were also included in the computational experiments. Computational results show that the proposed hybrid strategy improves convergence of sole genetic algorithm and provides a competitive alternative for the RCPSP. The computational experiments also reveal the limitations of the project management software for resource-constrained project scheduling." @default.
• W2079264914 created "2016-06-24" @default.
• W2079264914 creator A5051646144 @default.
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• W2079264914 date "2015-09-01" @default.
• W2079264914 modified "2023-10-16" @default.
• W2079264914 title "Hybrid Genetic Algorithm with Simulated Annealing for Resource-Constrained Project Scheduling" @default.
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• W2079264914 doi "https://doi.org/10.1061/(asce)me.1943-5479.0000323" @default.
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