The split heterogeneous vehicle routing problem with three-dimensional loading constraints on a large scale

Abstract

Abstract This paper introduces a complex real-world problem on a large scale that combines the split delivery heterogeneous vehicle routing problem with three-dimensional loading and considers new routing and loading constraints. The problem aims to find a set of routes with minimum transportation cost by satisfying the demand of all customers and loading constraints. We propose a column generation-based heuristic algorithm that employs three heuristic algorithms to solve the subproblem and a hybrid algorithm for loading. Computational experiments on the literature instances indicate that the proposed algorithm can produce very near solutions to the literature algorithm s solutions in significantly shorter running times. This paper introduces real-world instances with 230 to 850 customers, several times larger than the existing benchmarks. The results of the proposed algorithm for real-world instances are effective, and compared to the current situation, it leads to a reduction of 20% in the average total cost of transportation. Also, the average number of vehicles is reduced by 36%.