Parallel batching with multi-size jobs and incompatible job families

Alessandro Druetto (), Erica Pastore () and Elena Rener ()
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Alessandro Druetto: Università di Torino
Erica Pastore: Politecnico di Torino
Elena Rener: Politecnico di Torino

TOP: An Official Journal of the Spanish Society of Statistics and Operations Research, 2023, vol. 31, issue 2, No 7, 440-458

Abstract: Abstract Parallel batch scheduling has many applications in the industrial sector, like in material and chemical treatments, mold manufacturing and so on. The number of jobs that can be processed on a machine mostly depends on the shape and size of the jobs and of the machine. This work investigates the problem of batching jobs with multiple sizes and multiple incompatible families. A flow formulation of the problem is exploited to solve it through two column generation-based heuristics. First, the column generation finds the optimal solution of the continuous relaxation, then two heuristics are proposed to move from the continuous to the integer solution of the problem: one is based on the price-and-branch heuristic, the other on a variable rounding procedure. Experiments with several combinations of parameters are provided to show the impact of the number of sizes and families on computation times and quality of solutions.

Keywords: Parallel batch scheduling; Column generation; Incompatible job families; Multi-size jobs; 90C27; 90B35; 90C39 (search for similar items in EconPapers)
Date: 2023
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DOI: 10.1007/s11750-022-00644-2

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