Decision model for the customer order decoupling point considering order insertion scheduling with capacity and time constraints in logistics service supply chain

Liu, Weihua; Wu, Runze; Liang, Zhicheng; Zhu, Donglei

doi:10.1016/j.apm.2017.09.027

Cited by 22 publications

(18 citation statements)

References 68 publications

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“…In algorithm application, Liu et al [35] established a multi-objective programming model of LSSC and obtained the minimum operating cost and the highest service satisfaction value by using a sequential optimization algorithm. Liu et al [36] explored how a new inserted order affects the LSIs decision regarding the location of the customer order decoupling point by using genetic algorithms based on multiple datasets.…”

Section: Application Of Game Theory and Decision Making Tools In Logisticsmentioning

confidence: 99%

Green Logistics Service Supply Chain Games Considering Risk Preference in Fuzzy Environments

Wang

2021

Sustainability

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The increasing pressures from environmental crises are responsible for the green and sustainable choices made in supply chain management. Green logistics service supply chain (LSSC) operations play a significant role in reducing the environmental burden of the supply chain, and the risk preferences of logistics enterprises lead to more uncertainties in the green management of LSSC. Much research has been limited to case studies of green LSSC, and the different combinations of risk preferences among LSSC participants have generally been ignored. This paper investigates the impact of the risk preference on the equilibrium behavior of an LSSC composed of one logistics service integrator (LSI) and one logistics service provider (LSP) under fuzzy decision environments. Considering the fact that the greening innovation cost and the parameters of the demand function are all characterized as fuzzy variables, the games between the LSI and LSP with different risk preferences were comprehensively proposed under three scenarios. Then, the optimal decisions of the LSP and LSI were drawn, and numerical examples are presented. The results show that an optimistic risk attitude can appropriately improve the greening level, price, and green innovation cost of logistics services, while both risk appetite and risk aversion can lead to an increase in the outsourcing price. Moreover, when the decision maker is risk neutral, the partner’s risk attitude has a significant effect on the value of the decision variables and the cost. Finally, the optimal profits of different risk preference behaviors between the LSI and LSP vary among the game models under fuzzy environments. Subsequently, we obtained three management insights. Total involvement and cooperation among participants were vital factors for an improvement in green management in the LSSC. Additionally, risk preference plays a key role in how LSSC participants make decisions under fuzzy environments. Additionally, a dominant position in the LSSC plays a crucial role in generating profit.

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Section: Application Of Game Theory and Decision Making Tools In Logisticsmentioning

confidence: 99%

Green Logistics Service Supply Chain Games Considering Risk Preference in Fuzzy Environments

Wang

2021

Sustainability

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“…In order to adapt to the increasingly fierce competitive environment and meet the diversified demands of customers, the logistics industry attaches much more importance to informatization and coordinated development. Logistics service integrators (LSI) and functional logistics service providers (FLSP) have adopted alliances and integration to form a logistics service supply chain [11], [18]. The basic structure of LSSC is a functional logistics service provider → logistics service integrator → manufacturing and retail enterprise model (e.g.…”

Section: A Logistics Service Supply Chainmentioning

confidence: 99%

Research on Logistics Service Supply Chain Information Sharing Mechanism in the Belt and Road Initiative

Zhang

Bai

et al. 2020

IEEE Access

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In the context of the Belt and Road Initiative (BRI), demand in informatization and coordinated logistics services is playing increasing attention to the frequent international trade transactions. Several authors have proposed models about supply chain information sharing focused on product supply chain to analyze the factors affecting the level of corporate information sharing and the relationship between the level of information sharing and corporate performance, etc. However, little is available to study on the decision-making issues of corporate information sharing in the service supply chain. This paper aims to reveal the possible impact of the government's infrastructure construction investment and government incentives on the logistics service supply chain in the logistics service supply chain under this theme. This paper constructs an evolutionary game model to explore the dynamic selection process of corporate information co-strategy, the logistics service supply chain composed of functional logistics service provider (FLSP) and logistics service integrator (LSI) taked as the research object. Numerical experiments show that the additional revenue of information sharing, revenue distributing coefficient, information sharing risk coefficient and the speculative income coefficient are closely to the probability of gamers' choosing information sharing; moreover, investment in government infrastructure construction is conducive to improving the initial willingness of logistics companies to implement information sharing in which the government's incentives for corporate information sharing behavior are directly proportional to the probability of logistics companies choosing information sharing. We discuss the practical implications of the proposed model, and the wider implications for improving the level of international logistics cooperation and the high-quality development of logistics enterprise informatization under the BRI.

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“…They studied a list of many critical factors such as delivery time, delivery cost, capacity, transportation, technology, product delivery service providers, logistic companies, government regulations, delivery channels, etc. (Zhang, Nemhauser, Sokol, Cheon and Keha, 2018; Zhang, Qin, Yu and Liang, 2018; Liu et al , 2018; Lu et al , 2016; Shankar et al , 2018; Zarbakhshnia et al , 2018; Shi et al , 2018). In these approaches, they do not consider individual customer differences.…”

Section: Introductionmentioning

confidence: 99%

Modeling of individual customer delivery satisfaction: an AutoML and multi-agent system approach

Wang

Barenji

et al. 2019

IMDS

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Purpose The purpose of this paper is to propose an automated machine learning (AutoML) and multi-agent system approach to improve overall product delivery satisfaction under limited resources. Design/methodology/approach An AutoML method is purposed to model delivery satisfaction of individual customer, and a heuristic method and multi-agent system are proposed to improve overall satisfaction under limited processing capability. A series of simulation experiments have been conducted to illustrate the effectiveness of the proposed methodology. Findings The simulated results show that the proposed method can effectively improve overall delivery satisfaction, especially when the demand of customer orders is highly fluctuating and when the customer satisfaction models are highly diversified. Practical implications The proposed framework provides a more dynamic and continuously improving way to model delivery satisfaction of individual customer, thereby supports companies to provide personalized services and develop scalable and flexible business at a lower cost, and ultimately improves the overall quality, efficiency and effectiveness of delivery services. Originality/value The proposed methodology utilizes AutoML and multi-agent system to model individual customer delivery satisfaction and improve the overall satisfaction. It can cooperate with the existing delivery resource planning methods to further improve customer delivery satisfaction. The authors propose an AutoML approach to model individual customer delivery satisfaction, which enables continuous update and improvements. The authors propose multi-agent system and a heuristic method to improve overall delivery satisfaction. The numerical results show that the proposed method can improve overall delivery satisfaction with limited processing capability.

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Decision model for the customer order decoupling point considering order insertion scheduling with capacity and time constraints in logistics service supply chain

Cited by 22 publications

References 68 publications

Green Logistics Service Supply Chain Games Considering Risk Preference in Fuzzy Environments

Green Logistics Service Supply Chain Games Considering Risk Preference in Fuzzy Environments

Research on Logistics Service Supply Chain Information Sharing Mechanism in the Belt and Road Initiative

Modeling of individual customer delivery satisfaction: an AutoML and multi-agent system approach

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