A tri-level programming model based on Conditional Value-at-Risk for three-stage supply chain management

Xu, Xinsheng; Meng, Zhiqing; Shen, Rui

doi:10.1016/j.cie.2013.07.012

Cited by 63 publications

(28 citation statements)

References 28 publications

(36 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Yang et al [48] expanded research to the supply chain level to analyse the supply chain coordination and sales discount strategies in a risk-averse setting. Furthermore, researchers have made innovations primarily in the supply chain structure, such as the three-tier [49] and dual-channel supply chains [50]. Yang et al [51], considering the supplier and the retailer to be risk averse, investigated the impact of firms' risk-averse attitudes on supply chain performance.…”

Section: Risk Aversionmentioning

confidence: 99%

Optimal Operation Strategies under a Carbon Cap-and-Trade Mechanism: A Capital-Constrained Supply Chain Incorporating Risk Aversion

Liu

Jiang

et al. 2020

Mathematical Problems in Engineering

View full text Add to dashboard Cite

Many small and medium enterprises (SMEs) with capital constraints often have no access or find it costly to obtain a loan from a bank; the retailer tends to borrow money from other enterprises in the supply chain by trade credit financing. We consider an emission-dependent supply chain with one emission-dependent manufacturer and one capital-constrained retailer in need of financing to explore the optimal operational and environmental strategies of a low-carbon supply chain under trade credit financing. We use a Stackelberg game model to depict the low-carbon supply chain. We analyse the optimal carbon-emission reduction effort, wholesale price, and order quantity in the equilibrium state. The impacts of key parameters, such as the retailer’s internal working capital, the manufacturer’s risk-aversion degree, and the carbon-trading price on the supply chain operation, are analysed. The results show that the retailer’s capital constraint causes the carbon-emission reduction effort, wholesale price, and order quantity to improve synchronously. The supply chain achieves a win-win outcome for both the manufacturer and the retailer when the capital-constrained retailer is funded via trade credit from the manufacturer. The in-depth development of financing is beneficial to the manufacturer but is a disadvantage for the retailer. When the initial carbon-emission quota is low, the manufacturer benefits from a relatively lower carbon-trading price. Otherwise, a higher carbon-trading price is better for the manufacturer. The “carbon-trading price trap” ensures that the retailer’s profit is minimal. We further investigate the scenario in which the manufacturer is risk averse and find that the retailer will purchase fewer products and that the manufacturer will gain less profit to decrease the carbon-emission reduction effort. The manufacturer’s risk aversion is unfavourable to both the economic and environmental outcomes of the whole supply chain. This research provides strategic support for a low-carbon supply chain to carry out operational decisions in the context of enterprise capital constraint. To examine the theoretical results, the data used in the existing literature are further used to simulate the corresponding conclusions. Our research enriches the existing supply chain finance literature and provides decision support for the supply chain core enterprise.

show abstract

Section: Risk Aversionmentioning

confidence: 99%

Optimal Operation Strategies under a Carbon Cap-and-Trade Mechanism: A Capital-Constrained Supply Chain Incorporating Risk Aversion

Liu

Jiang

et al. 2020

Mathematical Problems in Engineering

View full text Add to dashboard Cite

show abstract

“…An ant colony optimization-based approach was developed to solve the problem using ants to construct the routes and exact optimization to solve the production problem. Xu et al (2013) developed a tri-level programming model for the three-stage supply chain management based on the conditional value-at-risk (CVaR) measure of risk management. In this model, the supplier and the manufacturer, at the upper and the middle levels, maximize their own profits while at the bottom level, the retailer maximizes her CVaR of the expected profit.…”

Section: Decentralized Supply Chainmentioning

confidence: 99%

Optimizing decentralized production–distribution planning problem in a multi-period supply chain network under uncertainty

et al. 2017

View full text Add to dashboard Cite

Decentralized supply chain management is found to be significantly relevant in today's competitive markets. Production and distribution planning is posed as an important optimization problem in supply chain networks. Here, we propose a multi-period decentralized supply chain network model with uncertainty. The imprecision related to uncertain parameters like demand and price of the final product is appropriated with stochastic and fuzzy numbers. We provide mathematical formulation of the problem as a bi-level mixed integer linear programming model. Due to problem's convolution, a structure to solve is developed that incorporates a novel heuristic algorithm based on Kth-best algorithm, fuzzy approach and chance constraint approach. Ultimately, a numerical example is constructed and worked through to demonstrate applicability of the optimization model. A sensitivity analysis is also made.

show abstract

“…The decision process is repeatedly executed until the Stackelberg equilibrium among them is achieved. This hierarchical decision-making process often appears in many decentralized decision problems in the real world, such as supply chain management [4], resource allocation [5,6] and hierarchical production operations [7].…”

Section: Introductionmentioning

confidence: 99%

Solving tri-level programming problems using a particle swarm optimization algorithm

Han

Zhang

et al. 2015

2015 IEEE 10th Conference on Industrial Electronics and Applications (ICIEA)

View full text Add to dashboard Cite

Abstract-Tri-level programming, a special case of multilevel programming, arises to deal with decentralized decision-making problems that feature interacting decision entities distributed throughout three hierarchical levels. As tri-level programming problems are strongly NP-hard and the existing solution approaches lack universality in solving such problems, the purpose of this study is to propose an intelligence-based heuristic algorithm to solve tri-level programming problems involving linear and nonlinear versions. In this paper, we first propose a general tri-level programming problem and discuss related theoretical properties. A particle swarm optimization (PSO) algorithm is then developed to solve the tri-level programming problem. Lastly, a numerical example is adopted to illustrate the effectiveness of the proposed PSO algorithm.Keywords-tri-level programming; bi-level programming; computational intelligence; particle swarm optimization; KuhnTucker conditions.

show abstract

A tri-level programming model based on Conditional Value-at-Risk for three-stage supply chain management

Cited by 63 publications

References 28 publications

Optimal Operation Strategies under a Carbon Cap-and-Trade Mechanism: A Capital-Constrained Supply Chain Incorporating Risk Aversion

Optimal Operation Strategies under a Carbon Cap-and-Trade Mechanism: A Capital-Constrained Supply Chain Incorporating Risk Aversion

Optimizing decentralized production–distribution planning problem in a multi-period supply chain network under uncertainty

Solving tri-level programming problems using a particle swarm optimization algorithm

Contact Info

Product

Resources

About