DocumentCode
130476
Title
Task assignments in logistics by adaptive multi-criterion evolutionary algorithm with elitist selection
Author
Balicki, Jerzy
Author_Institution
Fac. of Electron., Telecommun. & Inf., Gdansk Univ. of Technol.Gdańsk, Gdańsk, Poland
fYear
2014
fDate
7-10 Sept. 2014
Firstpage
1287
Lastpage
1291
Abstract
An evolutionary algorithm with elitist selection and an immunological procedure has been developed for Pareto task assignment optimization in logistics. A multi-criterion optimization problem has been formulated for finding a set of efficient alternatives. Some criteria have been applied for evaluation of solutions: bottleneck machine workload, a machine cost, and a system performance. Moreover, some numerical experiments have been performed and the machine constraints have been respected.
Keywords
Pareto optimisation; genetic algorithms; logistics; Pareto task assignment optimization; adaptive multicriterion evolutionary algorithm; bottleneck machine workload; elitist selection; genetic algorithms; immunological procedure; logistics; machine cost; multicriterion optimization problem; system performance; Computational modeling; Logistics; Optimization;
fLanguage
English
Publisher
ieee
Conference_Titel
Computer Science and Information Systems (FedCSIS), 2014 Federated Conference on
Conference_Location
Warsaw
Type
conf
DOI
10.15439/2014F309
Filename
6933167
Link To Document