A Joint Optimization Model considering the Product User's Risk Preference for Supply System Disruption

Abstract

Logistics distribution is the terminal link that connects the manufacturer and product user and determines the efficiency of the manufacturer's service. Therefore, the disruption risk of the joint system is an essential factor affecting the product user experience. In this paper, while considering the product user's supply disruption risk preference (PUSDRP), a biobjective integer nonlinear programming (INLP) model with subjective cost-utility is proposed to solve the manufacturer's combined location routing inventory problem (CLRIP). According to the user's time satisfaction requirement, a routing change selection framework (RCSF) is designed based on the bounded rational behavior of the user. Additionally, the Lagrange Relaxation and Modified Genetic Algorithm (LR-MGA) is proposed. The LR method relaxes the model, and the MGA finds a compromise solution. The experimental results show that the biobjective cost-utility model proposed in this paper is effective and efficient. The RCSF based on user behavior is superior to the traditional expected utility theory model. The compromise solution provides a better solution for the manufacturer order allocation delivery combinatorial optimization problem. The compromise solution not only reduces the manufacturer's total operating cost but also improves the user's subjective utility. To improve the stability of cooperation between manufacturers and users, the behavior decision-making method urges manufacturers to consider product users' supply disruption risk preferences (PUSDRPs) in attempting to optimize economic benefits for the long term. This paper uses behavior decision-making methods to expand the ideas of the CLRIP joint system.