The Fourth-Party Logistics Routing Problem Using Ant Colony System-Improved Grey Wolf Optimization

• Published in: Journal of advanced transportation Vol. 2020; no. 2020; pp. 1 - 15
• Main Authors: Bi, Hualing, Gao, Mengying, Feng, Wenjing, Lu, Fuqiang, Wang, Suxin
• Format: Journal Article
• Language: English
• Published: Cairo, Egypt Hindawi Publishing Corporation 15.10.2020; Hindawi; John Wiley & Sons, Inc; Wiley
• Subjects: Analysis; Ant colony optimization; Behavior; Carrying capacity; Customers; Decision making; Expected utility; Genetic algorithms; Logistics; Logistics management; Logistics services; Mathematical models; Nodes; Normal distribution; Operating costs; Optimization algorithms; Population; Risk aversion; Supply chains; Transit time; Transportation; Transportation planning; Utility theory
• ISSN: 0197-6729; 2042-3195; 2042-3195
• DOI: 10.1155/2020/8831746

The fourth-party logistics routing problem (4PLRP) is an important issue in the operation of fourth-party logistics (4PL). In this paper, the study of fourth-party logistics (4PL) path optimization considers that more third-party logistics (3PL) undertake transportation tasks. Under the condition that the 3PL transportation time, transportation cost, node transit time, and transit cost are uncertain, 4PL provides customers with a set of transportation solutions to transport transportation tasks from the initial node to the destination node according to the customer’s risk aversion preference. The transportation scheme not only meets the customer’s time and cost requirements but also meets the carrying capacity and reputation constraints of 3PL. Between the two nodes, one or more 3PLs will undertake the transportation task. The customer’s risk preference will be measured by the ratio utility theory (RUT). An ant colony system-improved grey wolf optimization (ACS-IGWO) is designed to solve the model, and the grey wolf optimization (GWO) is improved by the convergence factor and the proportional weight. Problem analysis is conducted through simulation experiments.