A Memetic Algorithm for Workforce Distribution in Dynamic Multi-Skill Call Centres

In this paper, we describe a novel approach for workforce distribution in dynamic multi-skill call centres. Dynamic multi-skill call centres require quick adaptations to a changing environment that only fast greedy heuristics can handle. The use of memetic algorithms, which are more complex than ad-hoc heuristics, can guide us to more accurate solutions. In order to apply memetic algorithms to such a dynamic environment, we propose a reformulation of the traditional problem, which combines predictions of future situations with a precise search mechanism, by enlarging the time-frame considered. Concretely, we propose a neural network for predicting call arrivals and the number of available agents, and a memetic algorithm to carry out the assignment of incoming calls to agents, which outperforms classical approaches to this dynamic environment. We also test our method on a real-world environment within a large multinational telephone operator.

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