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.
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Yamada, T., Yoshimura, K., Nakano, R. (1999). Information Operator Scheduling by Genetic Algorithms. In: McKay, B., Yao, X., Newton, C.S., Kim, JH., Furuhashi, T. (eds) Simulated Evolution and Learning. SEAL 1998. Lecture Notes in Computer Science(), vol 1585. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-48873-1_8
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DOI: https://doi.org/10.1007/3-540-48873-1_8
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