Inventory routing optimisation using differential evolution with feasibility checking and local search

Abstract

The inventory routing problem (IRP) is to minimise inventory and transportation costs simultaneously for increasing profitability of the system. However, the two costs are conflicting in most case and hard to solve. As a promising evolutionary algorithm, differential evolution (DE) has been successfully applied to solve many real-world optimisation problems, but we found that it is not used to optimise the IRP. In this paper, for the first time, we utilise the DE algorithm to optimise the one-to-many IRP (DEIR) where a product is shipped from supplier to a set of retailers over a planning period. In the proposed DEIR algorithm, the solution feasible checking method, the local search method and the optimal routing method based on DE are designed to suit the IRP solving. The computational tests have been conducted on 50 benchmark instances. Experimental results and comparison with different parameter settings have proved that the proposed algorithm is competitive.