Simulated annealing approach to solve dual resource constrained job shop scheduling problems: layout impact analysis on solution quality

Maurizio Faccio, Jana Ries and Nicola Saggiorno

International Journal of Mathematics in Operational Research, 2015, vol. 7, issue 6, 609-629

Abstract: Real-world manufacturing systems are operating subject to a substantial level of resource constraints. One characteristic model that considers the combination of human and machine resource constraints is called dual resource constrained (DRC). In this context a number of machines n_mach is managed by a selection of operators n_op, with typically n_op ≤ n_mach.. A real life case study for an Italian manufacturing company is introduced that uses a set of identical parallel machines being operated by a set of operators. Each job is scheduled to one machine with corresponding loading and unloading process times. A simulated annealing approach is proposed to solve the DRC job shop scheduling problem. A sensitivity analysis is conducted for a selection of algorithm-specific parameters used to solve characteristic DRC layouts. Being characteristic for the just-in-time (JIT) production environment, the high variability in job times has also been taken into account. The results show that the selected layout n_mach./n_op ratio strongly influences the production system performance. The impact of the ratio of constrained resources has been analysed for different layouts, showing that simulated annealing performs better for single resource constrained problems while also demonstrating that this trend is not symmetrical for different layouts, either operator or machine constrained.

Keywords: DRC scheduling; dual resource constrained; resource utilisation; JIT production; job list variability; simulated annealing; job shop scheduling; layout impact; Italy; manufacturing industry; parallel machine scheduling. (search for similar items in EconPapers)
Date: 2015
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