Open Access
ARTICLE
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,
Intelligent Automation & Soft Computing 2018, 24(1), 9-16. https://doi.org/10.1080/10798587.2016.1261956
Abstract
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.
Keywords
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. https://doi.org/10.1080/10798587.2016.1261956