General Variable Neighborhood Search for the Quote-Travelling Repairman Problem
Ha-Bang Ban · International Journal of Advanced Computer Science and Applications · 2020
The Quota-Travelling Repairman Problem (Q-TRP) tries to find a tour that minimizes the waiting time while the profit collected by a repairman is not less than a predefined value. The Q-TRP is an extended variant of the Travelling Repairman Problem (TRP). The problem is NP-hard problem; therefore, metaheuristic is a natural approach to provide near-optimal solutions for large instance sizes in a short time. Currently, several algorithms are proposed to solve the TRP. However, the quote constraint does not include, and these algorithms cannot be adapted to the Q-TRP. Therefore, developing an efficient algorithm for the Q-TRP is necessary. In this paper, we suggest a General Variable Neighborhood Search (GVNS) that combines with the perturbation and Adaptive Memory (AM) techniques to prevent the search from local optima. The algorithm is implemented with a benchmark dataset. The results demonstrate that good solutions, even the optimal solutions for the problem with 100 vertices, can be reached in a short time. Moreover, the algorithm is comparable with the other metaheuristic algorithms in accordance with the solution quality.