A genetic algorithm approach for location-inventory-routing problem with perishable products. (January 2017)

• Record Type: Journal Article
• Authors: Hiassat, Abdelhalim; Diabat, Ali; Rahwan, Iyad
• Is Part Of: Journal of manufacturing systems. Volume 42(2017)
• Page Start: 93
• Page End: 103
• Publication Date: 2017-01
• Subjects: Supply chain -- Facility location -- Vehicle routing -- Inventory management -- Perishable products -- Integer programming -- Genetic algorithms; Manufacturing processes -- Periodicals; Production engineering -- Data processing -- Periodicals; Robots, Industrial -- Periodicals; Production, Technique de la -- Informatique -- Périodiques; Robots industriels -- Périodiques; Electronic journals; 670.42
• DOI: 10.1016/j.jmsy.2016.10.004
• Languages: English
• ISSNs: 0278-6125

Abstract

Highlights: We develop a new optimization model that considers the three supply chain decision levels. We develop a GA that is capable of providing good solutions in reasonable computational time. We develop a novel chromosome representation that uses the special structure of the problem. Abstract: In this paper, we address a location-inventory-routing model for perishable products. The model determines the number and location of required warehouses, the inventory level at each retailer, and the routes traveled by each vehicle. The proposed model adds location decisions to a recently published inventory routing problem in order to make it more practical, thus supporting the prevalent claim that integration of strategic, tactical and operational level decisions produces better results for supply chains. Given that the model developed here is NP-hard, with no algorithm capable of finding its solution in polynomial time, we develop a Genetic Algorithm approach to solve the problem efficiently. This approach achieves high quality near-optimal solutions in reasonable time. Furthermore, the unique structure of the problem requires developing a new chromosome representation, as well as local search heuristics. Finally, an analysis is carried out to verify the effectiveness of the algorithm.