Abstract
Article history: Received September 16, 2014 Received in revised format: June 12, 2015 Accepted July 6, 2015 Available online July 8 2015 In this paper, group scheduling problem in no-wait flexible flowshop is considered by considering two stages with group sequence-dependent setup times and random breakdown of the machines. Genetic algorithm and simulated annealing based heuristics have been proposed to solve the problem. The primary objective of scheduling is to minimize the maximum completion time of the jobs for two classes of small and large scale problems. Computational results show that both GA and SA algorithms perform properly, but SA appeared to provide better results for both small and large scale problems. Growing Science Ltd. All rights reserved. 6 © 201
Highlights
Common manufacturing approaches are being replaced incessantly by new methods in order to improve the effectiveness and proficiency of the whole manufacturing system
According to the values obtained from Non- Parametric tests (Fig. 6 and Fig. 7) and obtained interval plot (Fig. 8), it can be concluded there was no significant differences between the obtained values from the proposed algorithms
We have investigated FF2(m1,m2)/nwt, fmls, Splc /Cmax problem considering random breakdown of the machines
Summary
Common manufacturing approaches are being replaced incessantly by new methods in order to improve the effectiveness and proficiency of the whole manufacturing system. All jobs in the same group require identical setup times on the machines. By grouping jobs into some groups, we can avoid many wasting times in the schedule. In a no-wait flowshop scheduling problem, it is assumed that n jobs are processed through m machines in a flowshop environment. When the process of a specific job begins on the first machine, it should constantly be processed without waiting in the line of any machine until its processing is completed on the last machine. Scheduling problems such as separable setup times are categorized into sequence-independent and sequence-dependent scheduling problems.
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