A Mathematical Programming Model with Equilibrium Constraints for Competitive Closed-Loop Supply Chain Network Design

2017 ◽  
Vol 34 (05) ◽  
pp. 1750026 ◽  
Author(s):  
Yuxiang Yang ◽  
Zuqing Huang ◽  
Qiang Patrick Qiang ◽  
Gengui Zhou
Keyword(s):  
Supply Chain ◽  
Mathematical Programming ◽  
Network Design ◽  
Closed Loop ◽  
Programming Model ◽  
Market Competition ◽  
Network Design Problem ◽  
Equilibrium Constraints ◽  
Mathematical Programming Model ◽  
Closed Loop Supply Chain

A firm sets up his facilities including manufacturing/remanufacturing plants and distribution/collection centers, incorporating an existing closed-loop supply chain (CLSC) network. The entering firm has to compete with the existing firms in the existing network. The entering firm behaves as the leader of a Stackelberg game while the existing firms in the existing network are followers. We assume that the entering firm can anticipate the existing firms’ reaction to his potential location decision before choosing his optimal policy. We use a CLSC network equilibrium model in which the decision makers are faced with multiple objectives to capture the existing firms’ reaction. A mathematical programming model with equilibrium constraints is developed for this competitive CLSC network design problem by taking into account the market competition existing in the decentralized CLSC network. A solution method is developed by integrating Genetic algorithm with an inexact logarithmic-quadratic proximal augmented Lagrangian method. Finally, numerical examples and the related results are studied for illustration purpose.

scholarly journals Fuzzy Bi-Objective Closed-Loop Supply Chain Network Design Problem with Multiple Recovery Options

2020 ◽  
Vol 12 (17) ◽  
pp. 6770
Author(s):  
Jian Zhou ◽  
Wenying Xia ◽  
Ke Wang ◽  
Hui Li ◽  
Qianyu Zhang
Keyword(s):  
Supply Chain ◽  
Network Design ◽  
Design Problem ◽  
Closed Loop ◽  
Solution Method ◽  
Network Design Problem ◽  
Closed Loop Supply Chain ◽  
Fuzzy Expected Value ◽  
Conflicting Objectives ◽  
Interactive Solution

A network design of a closed-loop supply chain (CLSC) with multiple recovery modes under fuzzy environments is studied in this article, in which all the cost coefficients (e.g., for facility establishment, transportation, manufacturing and recovery), customer demands, delivery time, recovery rates and some other factors that cannot be precisely estimated while designing are modeled as triangular fuzzy numbers. To handle these uncertain factors and achieve a compromise between the two conflicting objectives of maximizing company profit and improving customer satisfaction, a fuzzy bi-objective programming model and a corresponding two-stage fuzzy interactive solution method are presented. Applying the fuzzy expected value operator and fuzzy ranking method, the fuzzy model is transformed into a deterministic counterpart. Subsequently, Pareto optimal solutions are determined by employing the fuzzy interactive solution method to deal with the conflicting objectives. Numerical experiments address the efficiency of the proposed model and its solution approach. Furthermore, by comparing these results with the CLSC network design in deterministic environments, the benefits of modeling the CLSC network design problem with fuzzy information are highlighted.

scholarly journals Green closed-loop supply chain network design: a novel bi-objective chance-constraint approach

2021 ◽  
Vol 55 (2) ◽  
pp. 811-840
Author(s):  
Amin Reza Kalantari Khalil Abad ◽  
Seyed Hamid Reza Pasandideh
Keyword(s):  
Supply Chain ◽  
Network Design ◽  
Closed Loop ◽  
Programming Model ◽  
Expected Value ◽  
Chance Constraint ◽  
Chance Constrained Programming ◽  
Supply Chain Network Design ◽  
Supply Chain Network ◽  
Closed Loop Supply Chain

In this paper, a novel chance-constrained programming model has been proposed for handling uncertainties in green closed loop supply chain network design. In addition to locating the facilities and establishing a flow between them, the model also determines the transportation mode between facilities. The objective functions are applied to minimize the expected value and variance of the total cost CO2 released is also controlled by providing a novel chance-constraint including a stochastic upper bound of emission capacity. To solve the mathematical model using the General Algebraic Modeling System (GAMS) software, four multi-objective decision-making (MODM) methods were applied. The proposed methodology was subjected to various numerical experiments. The solutions provided by different methods were compared in terms of the expected value of cost, variance of cost, and CPU time using Pareto-based analysis and optimality-based analysis. In Pareto-based analysis, a set of preferable solutions were presented using the Pareto front; then optimality-based optimization was chosen as the best method by using a Simple Additive Weighting (SAW) method. Experimental experiments and sensitivity analysis demonstrated that the performance of the goal attainment method was 13% and 24% better that of global criteria and goal programming methods, respectively.

A Bi-Objective Stochastic Closed-loop Supply Chain Network Design Problem Considering Downside Risk

2017 ◽  
Vol 16 (3) ◽  
pp. 342-362 ◽  
Author(s):  
Fathollahi Fard Amir Mohammad ◽  
Fatemeh Gholian-Jouybari ◽  
Mahdi Paydar Mohammad ◽  
Hajiaghaei-Keshteli Mostafa
Keyword(s):  
Supply Chain ◽  
Network Design ◽  
Design Problem ◽  
Closed Loop ◽  
Downside Risk ◽  
Network Design Problem ◽  
Supply Chain Network Design ◽  
Supply Chain Network ◽  
Closed Loop Supply Chain
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