Part-grouping and build-scheduling with sequence-dependent setup time to minimize the makespan for non-identical parallel additive manufacturing machines

Author(s):  
Yong Jae Kim ◽  
Byung Soo Kim
2019 ◽  
Vol 2019 ◽  
pp. 1-16 ◽  
Author(s):  
Mustafa A. Qamhan ◽  
Ammar A. Qamhan ◽  
Ibrahim M. Al-Harkan ◽  
Yousef A. Alotaibi

An evolutionary discrete firefly algorithm (EDFA) is presented herein to solve a real-world manufacturing system problem of scheduling a set of jobs on a single machine subject to nonzero release date, sequence-dependent setup time, and periodic maintenance with the objective of minimizing the maximum completion time “makespan.” To evaluate the performance of the proposed EDFA, a new mixed-integer linear programming model is also proposed for small-sized instances. Furthermore, the parameters of the EDFA are regulated using full factorial analysis. Finally, numerical experiments are performed to demonstrate the efficiency and capability of the EDFA in solving the abovementioned problem.


2011 ◽  
Vol 339 ◽  
pp. 332-335 ◽  
Author(s):  
Parinya Kaweegitbundit

This paper considers flow shop scheduling problems with sequence dependent setup time. The makespan criterion has been considered. In this paper presented a comparison of three heuristics for solves this problem. The memetic algorithm, genetic algorithm and NEH heuristic have been compared. In the experimental, the result from memetic algorithm is maximum the best solution. Therefore, the MA heuristic outperforms other heuristic.


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