Routing optimization of fourth party logistics with reliability constraints based on Messy GA

Abstract

Purpose: The purpose of this paper is to choose a optimal routing in fourth party logistics (4PL) with the objective of transportation cost minimization under reliability level constraint. Design/methodology/approach: Reliability theory is applied to routing optimization problem. A mathematical model of the 4PL routing optimization problem with reliability constraints is built, which aims to find a route at the minimum cost. Due to the 4PL routing problem is NP-hard, two algorithms are designed: Messy Genetic Algorithm (Messy GA) and Enumeration Algorithm (EA). Findings: Through the model and algorithm, 4PL company can obtain the optimal solution quickly and effectively, according to customer’s reliability requirements. Practical implications: We give an example for test the effectiveness of the method and the algorithm. Originality/value: In this paper, we put objective factors that cause disturbances of transportation time into consideration, and reliability theory is applied to 4PL routing optimization problem. A Messy GA with double arrays encoding method is designed to solve the problem.