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.
Highlights
Uncertainty leads to supply disruption and cost increases, further burdening the global supply chain. e fourth wave Delta variant has caused a backlog of orders and transportation delays in many regions, thereby creating new obstacles to the recovery of the global supply chain. e global circulation of raw materials, parts, and consumer goods is threatened
Erefore, this paper uses a utility function to analyze product users’ risk preferences to help manufacturers use the benefits of a product user routing change selection framework to absorb or reduce the loss caused by disruption
This paper finds that interruptions and product users’ risk preferences importantly affect the uncertainty optimization of discrete networks. is paper contributes to the cost-utility biobjective integer nonlinear programming model to accurately describe the integrated location routing inventory optimization problem in discrete networks and quantify the subjective risk preference of product users. e model used in this paper helps manufacturers predict the choice preference of product users for disruption response schemes and optimize the biobjectives of minimizing economic cost input and maximizing product user utility
Summary
Erefore, this paper uses a utility function to analyze product users’ risk preferences to help manufacturers use the benefits of a product user routing change selection framework to absorb or reduce the loss caused by disruption. Is paper contributes to the cost-utility biobjective integer nonlinear programming model to accurately describe the integrated location routing inventory optimization problem in discrete networks and quantify the subjective risk preference of product users. E model used in this paper helps manufacturers predict the choice preference of product users for disruption response schemes and optimize the biobjectives of minimizing economic cost input and maximizing product user utility.
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