Genetic algorithm solving the orienteering problem with time windows

Abstract

The Orienteering Problem with Time Windows (OPTW) is a well-known routing problem in which a given positive profit and time interval are associated with each location. The solution to the OPTW finds a route comprising a subset of the locations, with a fixed limit on length or travel time, that maximises the cumulative score of the locations visited in the predefined time intervals. This paper proposes a new genetic algorithm (GA) for solving the OPTW. We use specific mutation based on the idea of insertion and shake steps taken from the well-known iterated local search method (ILS). Computational experiments are conducted on popular benchmark instances. The tests show that repetition of the mutation step for the same route during one iteration of GA can improve the solution so that it outperforms the ILS result.