Abstract
An S-stage hybrid (or flexible) flow shop, with sequence-independent uniform set-up times, parallel batching machines with compatible parallel batch families (like in casting or heat treatments in furnaces, chemical or galvanic baths, painting in autoclave, etc.) has been analysed with the purpose of reducing the number of tardy jobs (and the makespan); in Graham’s notation: FPB(m1, m2, …, mS)|p-batch, . Jobs are sorted dynamically (at each new delivery); batches are closed within sliding (or rolling) time windows and processed in parallel by multiple identical machines. Computation experiments have shown the better performance on benchmarks of the two proposed heuristics based on new formulations of the critical ratio (CRsetup) considering the ratio of allowance set-up and processing time in the scheduling horizon, which improves the weighted modified operation due date rule.
Highlights
This work considers a non-permutation hybrid flowshop, with sequence-independent uniform setup times, parallel batching machines with compatible parallel batch families
Two new heuristics have been proposed for the non-permutation hybrid flowshop scheduling problem, with parallel batching machines, compatible parallel batch families and manual machine loading modeled as sequence-independent uniform setup times, with the purpose of reducing the number of tardy jobs
The job priority depends on an innovative formulation of the critical ratio (CRsetup) of the available time between current time and due date versus the remaining processing time, according to two heuristics which consider respectively individual stages or all stages
Summary
This work considers a non-permutation hybrid (or flexible) flowshop, with sequence-independent uniform setup times, parallel batching machines with compatible parallel batch families. The model briefly recalled below is a two-stage non-permutation hybrid flowshop, with sequenceindependent uniform setup times, parallel batching machines and compatible parallel batch families, which is extended to S stages. It has been derived from a real case, the central sterile services of a large hospital, proposed by the authors (Rossi et al, 2013). Results can be extended to other sterilization plants, continuous casting (steel making), coating (heat and galvanic treatments, painting) etc Investigating this scheduling problem is important as it affects the logistics targets with due date reliability/no tardy jobs and high capacity utilization and low inventory levels. A mixed integer linear programming model (MILP) is available in Rossi et al (2013), along with the related literature
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