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Showing 2 results for Flexible Flow Shop
A New Lower Bound for Flexible Flow Shop Problem with Unrelated Parallel Machines
Nasim Nahavandi, Ebrahim Asadi Gangraj,
Volume 25, Issue 1 (2-2014)
Abstract
Flexible flow shop scheduling problem (FFS) with unrelated parallel machines contains sequencing in flow shop where, at any stage, there exists one or more processors. The objective consists of minimizing the maximum completion time. Because of NP-completeness of FFS problem, it is necessary to use heuristics method to address problems of moderate to large scale problem. Therefore, for assessment the quality of this heuristic, this paper develop a global lower bound on FFS makespan problems with unrelated parallel machines.
A Simultaneous Worker Assignment and Scheduling Problem to Minimize Makespan in Flexible Flow Shop via Metaheuristic Approaches
Ebrahim Asadi-Gangraj, Fatemeh Bozorgnezhad, Mohammad Mahdi Paydar,
Volume 30, Issue 2 (6-2019)
Abstract
In many real scheduling situations, it is necessary to deal with the worker assignment and job scheduling together. However, in traditional scheduling problems, only the machine is assumed to be a constraint and there isn’t any constraint about workers. This assumption could be due to the lower cost of workers compared to machines or the complexity of workers' assignment problems. This research proposes a flexible flow shop scheduling problem with two simultaneous issues: finding the best worker assignment, and solving the corresponding scheduling problem. We present a mathematical model that extends flexible flow shop scheduling problem to admit the worker assignment. Due to the NP-hardness of the research problem, two approximation approaches based on particle swarm optimization, named PSO and SPSO, are applied to minimize the makespan. The experimental results show that the proposed algorithms can efficiently minimize the makespan but the SPSO generates better solutions especially for large-size problems.
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