Task Assignments in Logistics by Adaptive Multi-Criterion Evolutionary Algorithm with Elitist Selection - Publication - Bridge of Knowledge

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Task Assignments in Logistics by Adaptive Multi-Criterion Evolutionary Algorithm with Elitist Selection

Abstract

An evolutionary algorithm with elitist selection has been developed for finding Pareto-optimal task assignments in logistics. A multi-criterion optimization problem has been formulated for finding a set of Pareto- optimal solutions. Three criteria have been applied for evaluation of task assignment: the workload of a bottleneck machine, the cost of machines, and the numerical performance of system. The machine constraints have been respected.

Citations

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Keywords

Details

Category:
Other
Type:
supllement, wydanie specjalne, dodatek
Published in:
Annals of Computer Science and Information Systems no. 2, pages 1287 - 1291,
ISSN: 2300-5963
Title of issue:
Proceedings of the 2014 Federated Conference on Computer Science and Information Systems strony 1287 - 1291
Language:
English
Publication year:
2014
DOI:
Digital Object Identifier (open in new tab) 10.15439/978-83-60810-58-3
Verified by:
Gdańsk University of Technology

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