Dual Flow Shops Scheduling with Family Setup Times
|關鍵字:||排程;跨廠;雙流線型生產;工件族;整備時間;交期;基因演算法;scheduling;cross-plant;dual flow shop;family;setup time;due date;genetic algorithm(GA)|
This research examines a dual flow shop scheduling problem, which is in the context of considering cross-plant processing and setup times. The scheduling objective is to minimize coefficient of variation of slack times, in which the slack time of a job denotes the difference between the due date and its total processing time. Herein, a set of jobs that need the same setup is called a job family. Most prior literature either used a family-based approach (all jobs of a particular family are scheduled as a single job) or used an individual-based approach (each job is independently scheduled without considering its affiliation to its job family). This research proposes a group-based approach (that is, dividing a job family into several job groups, and scheduling each job group as a single entity). Several genetic algorithms (GAs), which are of GA-EDD-Family, GA-EDD-Group, or GA-EDD-Individual, have been developed and compared by numerical experiments. Experiment results indicate that the group-based approach outperforms the other two approaches in most scenarios.
|Appears in Collections:||Thesis|
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