A Model for Planning TELCO Work-Field Activities Enabled by Genetic and Ant Colony Algorithms.

João Henriques; Filipe Caldeira

doi:10.9781/ijimai.2022.08.011

Authors

João Henriques Polytechnic Institute of Viseu
Filipe Caldeira Polytechnic Institute of Viseu

DOI:

https://doi.org/10.9781/ijimai.2022.08.011

Keywords:

Ant Colony Optimization, Genetic Algorithms, Optimization, Telecommunication

Supporting Agencies

This work was partially funded by the European Social Fund, through the Regional Operational Program Centro 2020, within the scope of the projects UIDB/05583/2020 and CISUC UID/CEC/00326/2020. Furthermore, we would like to thank the Research Center in Digital Services (CISeD) and the Polytechnic of Viseu for their support.

Abstract

Telecommunication Company’s (TELCO) are continuously delivering their efforts on the effectiveness of their daily work. Planning the activities for their workers is a crucial sensitive, and time-consuming task usually taken by experts. This plan aims to find an optimized solution maximizing the number of activities assigned to workers and minimizing the inherent costs (e.g., labor from workers, fuel, and other transportation costs). This paper proposes a model that allows computing a maximized plan for the activities assigned to their workers, allowing to alleviate the burden of the existing experts, even if supported by software implementing rule-based heuristic models. The proposed model is inspired by nature and relies on two stages supported by Genetic and Ant Colony evolutionary algorithms. At the first stage, a Genetic Algorithms (GA) identifies the optimal set of activities to be assigned to workers as the way to maximize the revenues. At a second step, an Ant Colony algorithm searches for an efficient path among the activities to minimize the costs. The conducted experimental work validates the effectiveness of the proposed model in the optimization of the planning TELCO work-field activities in comparison to a rule-based heuristic model.

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