This paper addresses a variant of the classical Traveling Salesman Problem known as Close-Enough Traveling Salesman Problem . In this problem, there is a set of nodes (customers, targets), each of them associated with a region, denoted as neighborhood, that contains it. The goal is to determine the shortest tour that visits all the nodes, where a node is visited when the tour traverses or reaches the region associated with the node. We propose a genetic algorithm (GA), which uses several strategies to optimize the tour, such as 2opt, second-order cone programming, and a bisection algorithm. The proposed approach is tested on 62 benchmark instances.
DI PLACIDO, A., ARCHETTI, C. et CERRONE, C. (2022). A genetic algorithm for the close-enough traveling salesman problem with application to solar panels diagnostic reconnaissance. Computers & Operations Research, 145, pp. 105831.