Information Operator Scheduling by Genetic Algorithms

Authors:
Takeshi Yamada;Kazuyuki Yoshimura;Ryohei Nakano
Affiliations:
-;-;-
Venue:
SEAL'98 Selected papers from the Second Asia-Pacific Conference on Simulated Evolution and Learning on Simulated Evolution and Learning
Year:
1998

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Abstract

In this paper, we discuss an approach to an operator scheduling problem in a large organization over time with the aim of maintaining service quality and reducing total labor costs. We propose a genetic algorithm (GA) with a parameterized fitness function inspired by homotopy methods and with null mutation to handle a variable number of operators. The proposed method is applied to the practical problem of scheduling operators in a telephone information center. Experimental results show that the proposed method performs consistently better than a GA method previously developed.