Authors:
David Millán-Ruiz
1
;
J. Ignacio Hidalgo
2
and
Josefa Díaz
3
Affiliations:
1
Telefonica Research & Development, Spain
;
2
Complutense U. of Madrid, Spain
;
3
University of Extremadura, Spain
Keyword(s):
Memetic algorithms, Variable neighbourhood search, Iterated local search, Simulated annealing.
Related
Ontology
Subjects/Areas/Topics:
Artificial Intelligence
;
Biocomputing and Complex Adaptive Systems
;
Computational Intelligence
;
Evolution Strategies
;
Evolutionary Computing
;
Genetic Algorithms
;
Informatics in Control, Automation and Robotics
;
Intelligent Control Systems and Optimization
;
Soft Computing
Abstract:
Call centre technology requires the assignment of a large volume of incoming calls to agents with the required skills to process them. In order to determine the right assignment among incoming calls and agents for a real production environment, a comparative study of meta-heuristics has been carried out. The aim of this study is to implement and empirically compare various representative meta-heuristics, which represent distinct search strategies to reach accurate, feasible solutions, for two different instances of the workforce distribution problem. This study points out how memetic algorithms can outperform other acknowledged meta-heuristics for two different problem instances from a real multi-skill call centre from one of the world's largest telecommunications companies.