Hybridized ant colony algorithm for the Multi Compartment Vehicle Routing Problem

Multi Compartment Vehicle Routing Problem is an extension of the classical Capacitated Vehicle Routing Problem where different products are transported together in one vehicle with multiple compartments. Products are stored in different compartments because they cannot be mixed together due to differences in their individual characteristics. The problem is encountered in many industries such as delivery of food and grocery, garbage collection, marine vessels, etc. We propose a hybridized algorithm which combines local search with an existent ant colony algorithm to solve the problem. Computational experiments are performed on new generated benchmark problem instances. An existing ant colony algorithm and the proposed hybridized ant colony algorithm are compared. It was found that the proposed ant colony algorithm gives better results as compared to the existing ant colony algorithm.NSERCScopu

Vehicle routing problem in omni-channel retailing distribution systems

This paper introduces a variant of the vehicle routing problem where a group of retail stores are served from a distribution center using a fleet of vehicles. Moreover, products are distributed to consumers from some of these retail stores based on product availability at inventory and by means of the same fleet of vehicles. This variant of the vehicle routing problem can be found in omni-channel retail distribution systems. Retail distribution systems are considered omni- or multi-channel systems when consumers can either place orders online or physically visit the stores to buy the products. In this problem, the decisions of assigning consumers to retail stores based on inventory availability are combined with finding the routes of vehicles. The new problem can be considered a generalization of both capacitated vehicle routing problem and the pickup and delivery problem. The paper presents a mathematical formulation to describe this problem and proposes two solution approaches (two-phase heuristic and multi-ant colony algorithm). We also generate new benchmark problem instances to evaluate the performance of the proposed solution approaches. 2017 Elsevier B.V.The authors acknowledge the funding received from the University of Manitoba and the NSERC discovery grants to support this research. The authors thank the anonymous referees for their valuable comments.Scopu