Impact of Iterated Local Search Heuristic Hybridization on Vehicle Routing Problems: Application to the Capacitated Profitable Tour Problem

The present paper highlights the impact of heuristic hybridization on Vehicle Routing Problems (VRPs). More specifically, we focus on the hybridization of the Iterated Local Search heuristic (ILS). We propose different hybridization levels for ILS with two other heuristics, namely a Variable Neighborhood Descent with Random neighborhood ordering (RVND) and a Large Neighborhood Search heuristic (LNS). To evaluate the proposed approaches, we test them on a variant of VRPs called the Capacitated Profitable Tour Problem (CPTP). In a CPTP, the visit of all customers is no longer required and the visit of each customer generates a specific profit. The available fleet of vehicle is limited and capacitated. The aim of the CPTP is to choose which set of customers to visit and in which order to maximize the difference between collected profits and routing costs. Our experiments show that the more ILS is hybridized the better are the results. To bring out the effectiveness of the proposed hybrid approach combining ILS, RVND and LNS, a comparison is made between that proposed approach and three local search heuristics from the literature of the CPTP. The obtained results are competitive.