A genetic algorithm based heuristic for scheduling of virtual manufacturing cells (VMCs)

Document Type

Article

Publication Date

6-1-2010

Abstract

We present a genetic algorithm (GA) based heuristic approach for job scheduling in virtual manufacturing cells (VMCs). In a VMC, machines are dedicated to a part as in a regular cell, but machines are not physically relocated in a contiguous area. Cell configurations are therefore temporary, and assignments are made to optimize the scheduling objective under changing demand conditions. We consider the case where there are multiple jobs with different processing routes. There are multiple machine types with several identical machines in each type and are located in different locations in the shop floor. Scheduling objective is weighted makespan and total traveling distance minimization. The scheduling decisions are the (i) assignment of jobs to the machines, and (ii) the job start time at each machine. To evaluate the effectiveness of the GA heuristic we compare it with a mixed integer programming (MIP) solution. This is done on a wide range of benchmark problem. Computational results show that GA is promising in finding good solutions in very shorter times and can be substituted in the place of MIP model. © 2009 Elsevier Ltd. All rights reserved.

Identifier

71749103834 (Scopus)

Publication Title

Computers and Operations Research

External Full Text Location

https://doi.org/10.1016/j.cor.2009.10.006

ISSN

03050548

First Page

1148

Last Page

1156

Issue

6

Volume

37

Fund Ref

Türkiye Bilimsel ve Teknolojik Araştirma Kurumu

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