Paper Info
Title
Comparative Study of Meta-heuristics for Solving Flow Shop Scheduling Problem Under Fuzziness
Abstract
In this paper we propose a hybrid method, combining heuristics and local search, to solve flow shop scheduling problems under uncertainty. This method is compared with a genetic algorithm from the literature, enhanced with three new multi-objective functions. Both single objective and multi-objective approaches are taken for two optimisation goals: minimisation of completion time and fulfilment of due date constraints. We present results for newly generated examples that illustrate the effectiveness of each method.
Year
DOI
Venue
2007
10.1007/978-3-540-73053-8_55
IWINAC (1)
Keywords
Field
DocType
hybrid method,comparative study,flow shop scheduling problem,genetic algorithm,present result,multi-objective approach,new multi-objective function,optimisation goal,completion time,due date constraint,local search,meta heuristics,flow shop scheduling,fuzzy sets,objective function,fuzzy set
Mathematical optimization,Job shop scheduling,Computer science,Flow shop scheduling,Fuzzy set,Heuristics,Minimisation (psychology),Artificial intelligence,Local search (optimization),Machine learning,Genetic algorithm,Metaheuristic
Conference
Volume
ISSN
Citations 
4527
0302-9743
2
PageRank 
References 
Authors
0.39
7
3
Name
Order
Citations
PageRank
Noelia González120.39
Camino R. Vela234631.00
Inés González-Rodríguez311510.73