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Publication detail
ŠEDA, M.
Original Title
Mixed Integer Programming vs. Genetic Algorithm Approach to Scheduling Permutation Flow Shop
Type
book chapter
Language
English
Original Abstract
Flow shop scheduling problems represent scheduling a set of jobs (composed of tasks) in shops with a product machine layout. Thus, the jobs have the same manufacturing order. A permutation flow shop scheduling problem (PFSSP) is a special version of the problem where each machine processes the jobs in the same order. In this paper, two different approaches to PFSSP with makespan objective are investigated. First a mixed integer programming model is formulated and it is used for solving the problem by an optimisation package GAMS. Since the problem belongs to NP-complete problems, this approach is limited to smaller instances. Its reasonable bounds are indicated using benchmarks from OR-Library. For large instances, an approach using genetic algorithm is proposed including its appropriate parameter settings. Computational results show a good performance of genetic algorithm. For suitable parameter settings presented in the paper, this approach is able to find the optimal solution almost in all cases or at least a solution very close to optimum when the test is executed several times.
Key words in English
permutation flow shop, integer programming, NP-complete problems, stochastic heuristics, genetic algorithm
Authors
RIV year
2005
Released
1. 10. 2005
Publisher
DAAAM International
Location
Wien (Austria)
ISBN
3-901509-43-7
Book
Katalinic, B. (ed.): DAAAM International Scientific Book 2005
Edition
DAAAM International Scientific Book
1726-9687
Periodical
State
Republic of Austria
Pages from
579
Pages to
590
Pages count
12
BibTex
@inbook{BUT55413, author="Miloš {Šeda}", title="Mixed Integer Programming vs. Genetic Algorithm Approach to Scheduling Permutation Flow Shop", booktitle="Katalinic, B. (ed.): DAAAM International Scientific Book 2005", year="2005", publisher="DAAAM International", address="Wien (Austria)", series="DAAAM International Scientific Book", pages="12", isbn="3-901509-43-7" }