Two-phase optimization approach for maintenance workforce planning in power distribution utilities

Abstract

This work addresses the maintenance workforce planning in electric power distribution utilities. A two-phase optimization procedure is proposed to consider the strategic (long-term) and tactical/operational (medium/short-term) planning. In the first phase (strategic planning), a bi-objective optimization problem is solved to locate depots and to size the number of repair teams at each depot. One of the objectives includes operating and capital expenses, while the other one is based on continuity indicators related to the interruption in the electrical energy supply. In order to solve this problem, we use a memetic algorithm which combines a metaheuristic with a mixed-integer linear programming (MILP) model. On the other hand, the second phase (tactical/operational planning) consists of solving other MILP model to determine, for each depot, the required number of electricians (now based on more detailed forecasts) and define their work schedules, minimizing the wage costs and hiring/firing expenses. The results show that a larger number of solutions can be found through the memetic algorithm compared to the purely metaheuristic approach. The proposed optimization algorithm is part of an innovative web-based system developed during a research and development project and it is now available for eleven Brazilian power distribution utilities.