Hybridized ant colony algorithm for the Multi Compartment Vehicle Routing Problem

Hybridized ant colony algorithm has been proposed to solve the Multi Compartment Vehicle Routing Problem.Numerical experiments were performed to evaluate the performance of the algorithm.The numerical results showed that the average total length improvement of the proposed HAC over the existing ACS is 5.1%. In addition, the proposed HAC maintains its high performance in large problems on contrary of the existing ACS.The numerical result for the effect of hybridizing the ant colony algorithm with local search schemes has been presented.Illustration of the benefit of using two-compartment vehicles instead of single-compartment vehicles has been presented. 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.