Job Scheduling in Virtual Manufacturing Cells with Lot-Streaming Strategy: A New Mathematical Model Formulation and a Genetic Algorithm Approach

13 Pages Posted: 21 Apr 2012  

S. E. Kesen

affiliation not provided to SSRN

Z. Güngör

affiliation not provided to SSRN

Date Written: May 2012

Abstract

This paper discusses the job scheduling problem in virtual manufacturing cells (VMCs) with the objective of makespan minimization. In the VMC scheduling problem, each job undergoes different processing routes and there is a set of machines to process any operation. Jobs are produced in lot and lot-streaming is permitted. In addition, machines are distributed through the facility, which raises the travelling time issue. For this reason, the decisions are machine assignments, starting times and sub-lot sizes of the operations. We develop a new Mixed Integer Linear Programming (MILP) formulation that considers all aspects of the problem. Owing to the intractability matter, it is unlikely that the MILP could provide solutions for big-sized instances within a reasonable amount of time. We therefore present a Genetic Algorithm (GA) with a new chromosome structure for the VMC environment. Based on a wide range of examinations, comparative results show that GA is quite favourable and that it obtains the optimum solution for any of the instances in the case where sub-lot number equals 1.

Suggested Citation

Kesen, S. E. and Güngör, Z., Job Scheduling in Virtual Manufacturing Cells with Lot-Streaming Strategy: A New Mathematical Model Formulation and a Genetic Algorithm Approach (May 2012). Journal of the Operational Research Society, Vol. 63, Issue 5, pp. 683-695, 2012. Available at SSRN: https://ssrn.com/abstract=2043008 or http://dx.doi.org/10.1057/jors.2011.86

S. E. Kesen (Contact Author)

affiliation not provided to SSRN ( email )

No Address Available

Z. Güngör

affiliation not provided to SSRN

No Address Available

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