An Intelligent Cooperative Approach Applied to Single Machine Total Weighted Tardiness Scheduling Problem
Year: 2017
Journal of Information and Computing Science, Vol. 12 (2017), Iss. 4 : pp. 270–279
Abstract
In this research work, we propose an intelligent search technique called genetic simulated annealing algorithm (GASA) to obtain an approximate solution to the single machine total weighted tardiness job scheduling problem, which is a strong NP-hard. The developed approach is based on two metaheuristics: genetic algorithm (GA) and simulated annealing (SA) algorithm. In this context, when GA is exploited as a global search strategy to discover solution space, SA algorithm is used as a local search technique to enhance more efficiently the visited attractive regions to improve solution quality. Numerical results using a set of benchmarks have shown the capability of the proposed method to produce better solutions compared to results given by some other recently literature works.
Journal Article Details
Publisher Name: Global Science Press
Language: English
DOI: https://doi.org/2024-JICS-22470
Journal of Information and Computing Science, Vol. 12 (2017), Iss. 4 : pp. 270–279
Published online: 2017-01
AMS Subject Headings:
Copyright: COPYRIGHT: © Global Science Press
Pages: 10