EURO 2024 Copenhagen
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3419. Scheduling electricity distribution field maintenance by a prize-collection VRP approach

Invited abstract in session TB-29: Applications of combinatorial optimisation in industry and services II, stream Combinatorial Optimization.

Tuesday, 10:30-12:00
Room: 157 (building: 208)

Authors (first author is the speaker)

1. Roberto Tavares
UFSCar
2. Arineia Assis
DEP/DAA, UFSCAR/IFG
3. Mario Batalha
Federal University of Sao Carlos
4. Roberto Martins
Federal University of Sao Carlos
5. Herick Moralles
Federal University of Sao Carlos

Abstract

Daily field maintenance activities are common in a wide range of service providers and industrial applications. Electricity distribution systems are a classical example, commonly characterized by a set of pending services that must be accomplished by a set of maintenance teams. There are three main daily decisions usually involved in the scheduling of such services: (i) what services will be executed on a specified date; (ii) what is the sequence of each service list of each maintenance team (usually based on routing constraints); (iii) which team will execute each set of services. In this research, we address a real-world problem faced by an electricity distribution company. In this case, there are a set of activities available to the maintenance teams. For each activity is assigned a "prize" (strongly related to the activity's nature and deadline). The time required to start an activity may be influenced by the previous task (e.g., there is no need to perform two security checks on activities executed at the same place). This problem is faced as a derivation of the prize-collection vehicle routing problem (PCVRP). This research presents a MILP formulation and proposes a meta-heuristic approach to generate daily maintenance schedules. Both solution strategies are applied to problem datasets based on historical data of large cities attended by the electricity distribution company. Our results show the applicability of the meta-heuristic to solve this real-world problem.

Keywords

Status: accepted

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