Ant Colony System for a Problem in Reverse Logistic

Distribution, redistribution, recycling and repacking have become an important issue in logistic planning during the last decades. While keeping operational cost as low as possible still the main goal for logistic planners, other aspects such as recycling are getting more attention from industry. In this article the well known Ant Colony System (ACS), a bio-inspired algorithm, is implemented to solve a problem arising in Reverse Logistic namely Vehicle Routing Problem with Simultaneous Delivery and Pickup (VRPSDP). To solve this problem we need to find the optimal set of paths that meet, at the same time, customer delivery and pickup demands. In order to solve this problem, our ACS implementation makes use of a strategy that mimics the effect of the pheromone in the natural Ants behaviour. To do that, each vehicle is viewed as an individual agent (ant) and consequently its behaviour is driven by pheromone strategy, i.e. it tends to choose the route for which the pheromone level is higher. Results show that our ACS implementation provides good quality solutions within an acceptable time. Furthermore, obtained solutions are quite competitive when compared to other stochastic techniques previously studied in literature.