Hybrid Genetic Algorithm with Simulated Annealing for Resource-Constrained Project Scheduling

Date

2015-09-01

Author

BETTEMİR, ÖNDER HALİS
Sönmez, Rifat

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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. (C) 2014 American Society of Civil Engineers.

Subject Keywords

Management Science and Operations Research, General Engineering, Strategy and Management, Industrial relations

URI

https://hdl.handle.net/11511/35322

Journal

JOURNAL OF MANAGEMENT IN ENGINEERING

DOI

https://doi.org/10.1061/(asce)me.1943-5479.0000323

Collections

Department of Civil Engineering, Article

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Citation Formats

Ö. H. BETTEMİR and R. Sönmez, “Hybrid Genetic Algorithm with Simulated Annealing for Resource-Constrained Project Scheduling,” JOURNAL OF MANAGEMENT IN ENGINEERING, pp. 0–0, 2015, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/35322.