Multiple orders per job batch scheduling with incompatible jobs |
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Authors: | Vishnu Erramilli Scott J Mason |
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Institution: | (1) Department of Industrial Engineering, University of Arkansas, 4207 Bell Engineering Center, Fayetteville, AR 72701, USA;(2) Optessa USA Inc., 2 Bridge Ave., Building 6 Galleria, Red Bank, NJ 07701, USA |
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Abstract: | The multiple orders per job (MOJ) scheduling problem is presented for the batch-processing environment such as that exemplified by diffusion ovens. A mixed-integer
programming formulation is presented for the incompatible job family case wherein only jobs that belong to the same family
may be grouped together in a production batch. This optimization formulation is tested through an extensive experimental design
with the objective of minimizing total weighted tardiness (maximizing on-time delivery performance). Optimal solutions are
achievable for this initial set of 6-to-12 order problems, but it is noted that the optimization model takes an unreasonable
amount of computation time, which suggests the need for heuristic development to support the analysis of larger, more practical
MOJ batch scheduling problems. A number of simple heuristic approaches are investigated in an attempt to find near-optimal
solutions in a reasonable amount of computation time. It is seen that a combination of the heuristics produces near-optimal
solutions for small order problems. Further testing proves that these heuristic combinations are the best for large order
problems as well. |
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Keywords: | |
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