Abstract
We study the scheduling problem of minimising weighted completion times on parallel identical batching machines with dynamic job arrivals and incompatible job families. Each job is associated with a family, weight (priority), release time, and size. Batching machines can process simultaneously up to a specified total size of the jobs of a particular family. The scheduling problem can be represented by. We present a mathematical model and heuristic algorithms employing different local search procedures individually and sequentially under a variable neighbourhood search scheme. We have shown that among local searches, repositioning the batches instead of jobs yields better results. The best-performing heuristic algorithm is capable of generating solutions within 0.6% of the best overall heuristic solution for each instance in a reasonable amount of time. When this heuristic is compared against the mathematical model, solutions that are 3.7% above optimal on average in the 15-job problem instances are possible.
Original language | English (US) |
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Pages (from-to) | 2462-2477 |
Number of pages | 16 |
Journal | International Journal of Production Research |
Volume | 51 |
Issue number | 8 |
DOIs | |
State | Published - 2013 |
Keywords
- batch scheduling
- heuristics
- mathematical modelling
- scheduling
- variable neighbourhood search
ASJC Scopus subject areas
- Strategy and Management
- Management Science and Operations Research
- Industrial and Manufacturing Engineering