A case-injected genetic algorithm for single machine scheduling problems with release time

A case-injected genetic algorithm for single machine scheduling problems with release time

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Article ID: iaor20071185
Country: Netherlands
Volume: 103
Issue: 2
Start Page Number: 551
End Page Number: 564
Publication Date: Jan 2006
Journal: International Journal of Production Economics
Authors: , ,
Keywords: heuristics: genetic algorithms
Abstract:

This paper presents a case-injected genetic algorithm (CIGA) to solve the single machine scheduling problems with release time and the objective is to minimize the total weighted completion time. The initial case base is generated by using general genetic algorithm (GA) for different problem sets. To solve a new problem, CIGA first retrieves the similar cases from the case base according to the two-phase similarity coefficient adaptation procedure developed in this research, and then incorporates these similar cases into the GA to solve the problems at hand. Finally, CIGA stores the solved problems in the case base for future retrievals. Extensive experimental results, including case retrieval of case base as initial population and injection of case base every 600 generation, show that CIGA outperformed the other GAs with better quality of solutions.

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