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

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 t...

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Autores principales:	Yang Song, Yan-Qiu Liu, Qi Sun, Ming-Fei Chen, Hai-Tao Xu
Formato:	article
Lenguaje:	EN
Publicado:	Hindawi Limited 2021
Materias:	Engineering (General). Civil engineering (General) TA1-2040 Mathematics QA1-939
Acceso en línea:	https://doaj.org/article/46e38a016d0d4f35bbf90b3d8d459a34
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spelling	oai:doaj.org-article:46e38a016d0d4f35bbf90b3d8d459a342021-11-22T01:10:31ZA Joint Optimization Model considering the Product User's Risk Preference for Supply System Disruption1563-514710.1155/2021/5081753https://doaj.org/article/46e38a016d0d4f35bbf90b3d8d459a342021-01-01T00:00:00Zhttp://dx.doi.org/10.1155/2021/5081753https://doaj.org/toc/1563-5147Logistics 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.Yang SongYan-Qiu LiuQi SunMing-Fei ChenHai-Tao XuHindawi LimitedarticleEngineering (General). Civil engineering (General)TA1-2040MathematicsQA1-939ENMathematical Problems in Engineering, Vol 2021 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Engineering (General). Civil engineering (General) TA1-2040 Mathematics QA1-939
spellingShingle	Engineering (General). Civil engineering (General) TA1-2040 Mathematics QA1-939 Yang Song Yan-Qiu Liu Qi Sun Ming-Fei Chen Hai-Tao Xu A Joint Optimization Model considering the Product User's Risk Preference for Supply System Disruption
description	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.
format	article
author	Yang Song Yan-Qiu Liu Qi Sun Ming-Fei Chen Hai-Tao Xu
author_facet	Yang Song Yan-Qiu Liu Qi Sun Ming-Fei Chen Hai-Tao Xu
author_sort	Yang Song
title	A Joint Optimization Model considering the Product User's Risk Preference for Supply System Disruption
title_short	A Joint Optimization Model considering the Product User's Risk Preference for Supply System Disruption
title_full	A Joint Optimization Model considering the Product User's Risk Preference for Supply System Disruption
title_fullStr	A Joint Optimization Model considering the Product User's Risk Preference for Supply System Disruption
title_full_unstemmed	A Joint Optimization Model considering the Product User's Risk Preference for Supply System Disruption
title_sort	joint optimization model considering the product user's risk preference for supply system disruption
publisher	Hindawi Limited
publishDate	2021
url	https://doaj.org/article/46e38a016d0d4f35bbf90b3d8d459a34
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A Joint Optimization Model considering the Product User's Risk Preference for Supply System Disruption

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