Management Science Letters, Volume (2), No (1), Year (2012-5) , Pages (2011-2018)

Title : ( Optimizing combination of job shop scheduling and quadratic assignment problem through multi-objective decision making approach )

Authors: Mostafa Kazemi , SAEED POORMOAIED , ghasem eslami ,

Citation: BibTeX | EndNote

Abstract

In this paper, we consider job shop scheduling and machine location problem, simultaneously. Processing, transportation, and setup times are defined as deterministic parameters. The purpose of this paper is to determine machine location and job scheduling such that the make span and transportation cost is minimized. Therefore, the proposed model is a multi-objective problem one, where the first objective function minimizes make span and another minimizes the transportation cost. To solve the multi-objective problem, two methods are evaluated. Considering combination of job shop scheduling problem and machine location problem makes the proposed model more complex than job shop scheduling problem, which is an NP-hard problem. Therefore, to solve the proposed model, genetic algorithm as a meta-heuristic algorithm is implemented. To show the efficiency of the proposed genetic algorithm, 6×6 job shop scheduling problems are considered.

Keywords

, Job shop scheduling Quadratic assignment problem Multi, objective problem
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@article{paperid:1028676,
author = {Kazemi, Mostafa and POORMOAIED, SAEED and Eslami, Ghasem},
title = {Optimizing combination of job shop scheduling and quadratic assignment problem through multi-objective decision making approach},
journal = {Management Science Letters},
year = {2012},
volume = {2},
number = {1},
month = {May},
issn = {1923-9335},
pages = {2011--2018},
numpages = {7},
keywords = {Job shop scheduling Quadratic assignment problem Multi-objective problem},
}

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%0 Journal Article
%T Optimizing combination of job shop scheduling and quadratic assignment problem through multi-objective decision making approach
%A Kazemi, Mostafa
%A POORMOAIED, SAEED
%A Eslami, Ghasem
%J Management Science Letters
%@ 1923-9335
%D 2012

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