Paper Info
Title
Evolutionary clustering search for flowtime minimization in permutation flow shop
Abstract
This paper deals with the Permutation Flow Shop scheduling problem with the objective of minimizing total flow time, and therefore reducing in-process inventory. A new hybrid metaheuristic Genetic Algorithm - Cluster Search is proposed for the scheduling problem solution. The performance of the proposed method is evaluated and results are compared with the best reported in the literature. Experimental tests show the new method superiority for the test problems set, regarding the solution quality.
Year
DOI
Venue
2007
10.1007/978-3-540-75514-2_6
Hybrid Metaheuristics
Keywords
Field
DocType
evolutionary clustering search,new method superiority,flowtime minimization,genetic algorithm,new hybrid metaheuristic,solution quality,permutation flow shop scheduling,test problem,cluster search,experimental test,permutation flow shop,scheduling problem solution,flow shop scheduling,scheduling problem
Mathematical optimization,Job shop scheduling,Flow shop scheduling,Permutation,Minification,Evolutionary clustering,Local search (optimization),Mathematics,Genetic algorithm,Metaheuristic
Conference
Volume
ISSN
ISBN
4771
0302-9743
3-540-75513-6
Citations 
PageRank 
References 
11
0.85
13
Authors
3
Name
Order
Citations
PageRank
geraldo ribeiro filho1413.07
Marcelo Seido Nagano29812.52
Luiz Antonio Nogueira Lorena349836.72