A genetic algorithm with grouping selection and searching operators for the orienteering problem

Abstract

In the Orienteering Problem (OP), a set of linked vertices, each with a score, is given. The objective is to find a route, limited in length, over a subset of vertices that maximises the collective score of the visited vertices. In this paper, we present a new, efficient genetic algorithm (nGA) that solves the OP. We use a special grouping during selection, which results in better-adapted routes in the population. Furthermore, we apply a searching crossover to each generation, which uses the common vertices between distinct routes in the population; we also apply a searching mutation. Computer experiments on the nGA are conducted on popular data sets. In some cases, the nGA yields better results than well-known heuristics.