Two-stage hybrid flowshop scheduling with simultaneous processing machines

Bailin Wang (), Kai Huang and Tieke Li
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Bailin Wang: University of Science and Technology Beijing
Kai Huang: McMaster University
Tieke Li: University of Science and Technology Beijing

Journal of Scheduling, 2018, vol. 21, issue 4, No 1, 387-411

Abstract: Abstract Simultaneous processing machines, common in processing industries such as steel and food production, can process several jobs simultaneously in the first-in, first-out manner. However, they are often highly energy-consuming. In this paper, we study a new two-stage hybrid flowshop scheduling problem, with simultaneous processing machines at the first stage and a single no-idle machine with predetermined job sequence at the second stage. A mixed integer programming model is proposed with the objective of minimizing the total processing time to reduce energy consumption and improve production efficiency. We give a sufficient and necessary condition to construct feasible sequencing solutions and present an effective approach to calculate the time variables for a feasible sequencing solution. Based on these results, we design a list scheduling heuristic algorithm and its improvement. Both heuristics can find an optimal solution under certain conditions with complexity O(nlogn), where n is the number of jobs. Our experiments verify the efficiency of these heuristics compared with classical heuristics in the literature and investigate the impacts of problem size and processing times.

Keywords: Scheduling; Hybrid flowshop; Simultaneous processing machine; Heuristic; List scheduling (search for similar items in EconPapers)
Date: 2018
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Citations: View citations in EconPapers (1)

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DOI: 10.1007/s10951-017-0545-x

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