Improving simulated annealing with variable neighborhood search to solve the resource-constrained scheduling problem

Improving simulated annealing with variable neighborhood search to solve the resource-constrained scheduling problem

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Article ID: iaor20083761
Country: United Kingdom
Volume: 10
Issue: 6
Start Page Number: 375
End Page Number: 386
Publication Date: Dec 2007
Journal: Journal of Scheduling
Authors: ,
Keywords: heuristics: local search, heuristics: tabu search, optimization: simulated annealing
Abstract:

The purpose of this paper is to improve the simulated annealing method with a variable neighborhood search to solve the resource-constrained scheduling problem. We also compare numerically this method with other neighborhood search (local search) techniques: threshold accepting methods and tabu search. Furthermore, we combine these techniques with multistart diversification strategies and with the variable neighborhood search technique. A thorough numerical study is completed to set the parameters of the different methods and to compare the quality of the solutions that they generate. The numerical results indicate that the simulated annealing method improved with a variable neighborhood search technique is indeed the best solution method.

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