| Summary: | 碩士 === 國立雲林科技大學 === 工業工程與管理研究所碩士班 === 100 === This paper focuses on the flow shop scheduling with unrelated parallel machine and resource flexibility consideration, the processing time of each job may be reduced linearly by using of resource on unrelated parallel machine and sum of resource which each job uses limited to each level’s overall resource. The objective is minimizing makespan. The general flow shop scheduling problem is strongly NP-hard problem, add machine and resource’s consideration will make this problem difficulty.
Therefore, a hybrid genetic algorithm is developed to solve the proposed scheduling problem, this study first constructs mathematical integer programming model and proves this model by Lingo 11.0 and then uses Taguchi method to find the best parameters of genetic algorithms, finally evaluates algorithms’s efficiency with different scale tests of instances.The experimental results shows that the hybrid genetic algorithm by applying local search better than traditional genetic algorithm on all tests.
|
|---|
