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An Efficient Hybrid Algorithm for a Bi-objectives Hybrid Flow Shop Scheduling

S. M. Mousavia, M. Zandiehb

a Faculty of Industrial Engineering, Department of Technical and Engineering, Islamic Azad University, Noshahr Branch, Postal code 41433—46511, Mazandaran, Iran;
b Management and Accounting Faculty, Department of Industrial Management, Shahid Beheshti University, G. C., Tehran, Iran

* Corresponding Author: S. M. Mousavi, email

Intelligent Automation & Soft Computing 2018, 24(1), 9-16.


This paper considers the problem of scheduling n independent jobs in g-stage hybrid flow shop environment. To address the realistic assumptions of the proposed problem, two additional traits were added to the scheduling problem. These include setup times, and the consideration of maximum completion time together with total tardiness as objective function. The problem is to determine a schedule that minimizes a convex combination of objectives. A procedure based on hybrid the simulated annealing; genetic algorithm and local search so-called HSA-GA-LS are proposed to handle this problem approximately. The performance of the proposed algorithm is compared with a genetic algorithm proposed in the literature on a set of test problems. Several performance measures are applied to evaluate the effectiveness and efficiency of the proposed algorithm in finding a good quality schedule. From the results obtained, it can be seen that the proposed method is efficient and effective.


Cite This Article

S. M. Mousavi and M. Zandieh, "An efficient hybrid algorithm for a bi-objectives hybrid flow shop scheduling," Intelligent Automation & Soft Computing, vol. 24, no.1, pp. 9–16, 2018.

cc This work is licensed under a Creative Commons Attribution 4.0 International License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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