A memetic algorithm for solving rich waste collection problems

Abstract

Inspired by a real-life case in the Brussels Capital Region, Belgium, this paper provides a Memetic Algorithm with Sequential Split procedure (MASS) for solving a large variety of waste collection problems with multiple depots, a restricted vehicle fleet at each depot, multiple (intermediate) processing facilities, capacity restrictions per processing facility and partial pick-ups. MASS first generates satisfactory initial solutions which are feasible w.r.t. the shift duration and the vehicle capacity using a novel procedure in which (1) a giant tour is split into vehicle routes, (2) intermediate processing facilities are introduced and (3) waste pick-ups can be split further if profitable. Second, MASS improves these solutions through local search. New test instances are created, which are used to evaluate the performance of MASS’s components. We show that MASS provides high-quality feasible solutions by comparing MASS with an exact approach on a small example. Furthermore, MASS is tested on existing instances for the multiple-depot vehicle routing problem (MDVRP), (multi-depot) vehicle routing problem with intermediate facilities ((MD)VRPIF) and the multi-depot vehicle routing problem with inter-depot routes (MDVRPI). MASS shows competitive results for the MDVRP, the VRPIF and the MDVRPI. For the MDVRPIF, MASS obtains better results than those currently found in the literature. To assess its practical value, MASS is used to solve a real-life waste collection problem in the Brussels Capital Region in which alternative scenarios for municipal bio-waste collection and treatment are compared.