Inventory routing optimisation using differential evolution with feasibility checking and local search. (9th September 2019)

• Record Type: Journal Article
• Authors: Peng, Hu; Deng, Changshou; Peng, Shunxu
• Is Part Of: International journal of intelligent information and database systems. Volume 12:Number 1/2(2019)
• Page Start: 32
• Page End: 46
• Publication Date: 2019-09-09
• Subjects: differential evolution -- inventory routing problem -- feasible checking -- local search; Database management -- Computer programs -- Periodicals; Information retrieval -- Computer programs -- Periodicals; Information storage and retrieval systems -- Computer programs -- Periodicals; Artificial intelligence -- Periodicals; Expert systems (Computer science) -- Periodicals; Intelligent agents (Computer software) -- Periodicals; 006.33
• Languages: English
• ISSNs: 1751-5858

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.