Solve the IRP problem with an improved discrete differential evolution algorithm. (9th September 2019)

• Record Type: Journal Article
• Authors: Cheng, Shi; Wang, Zelin
• Is Part Of: International journal of intelligent information and database systems. Volume 12:Number 1/2(2019)
• Page Start: 20
• Page End: 31
• Publication Date: 2019-09-09
• Subjects: differential evolution algorithm -- inventory routing problem -- mutation factor -- crossover factor; 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 is a NP hard problem. It is difficult to find the optimal solution in polynomial time. Many scholars have studied it in many years. This paper analyses the inventory-routing optimisation problem, and comprehensive differential evolution algorithm is good performance in solving combinatorial optimisation problems. The differential evolution algorithm was improved to make it be suitable for solving discrete combination optimisation problems. In order to improve the performance of the differential evolution algorithm to solve the inventory routing problem, this paper puts forward dynamic adjustment of mutation factor and crossover factor of the differential evolution. It is proved by numerical experiments that the proposed algorithm has certain performance advantages, and it also proves that the improved algorithm can improve the performance of the algorithm by dynamic adjustment of the mutation factor and crossover factor.