Flexible Job-Shop Scheduling with Changeover Priorities

Holden Milne,Opeyemi Adesina, Russell Campbell, Barbara Friesen,Masud Khawaja

MACHINE LEARNING, OPTIMIZATION, AND DATA SCIENCE (LOD 2021), PT I(2022)

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摘要
In a job shop, operators run different machines concurrently, which obviously may result in multiple jobs being completed at the same time. It becomes a concern whenever jobs with lower priorities are serviced over jobs with higher priorities. Our goal is to generate up-to-date changeover schedules that prioritize servicing high-priority jobs without jeopardizing schedule optimality in real-time. We formulate flexible job-shop scheduling with changeover priorities (FJSCP) based on the knapsack model and develop an algorithm based on greedy methodology. Results show that depending on a pairwise combinations of pivot selection modes our method could save up to 53% in idle time and up to 12% in makespan when compared with the traditional FCFS baseline.
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关键词
Optimization problem, Operations research, Job scheduling, Job-shop problem, Scheduling problem
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