Selection of Transportation Channels in Closed-Loop Supply Chain Using Meta-Heuristic Algorithm

2020 ◽  
pp. 726-749
Author(s):  
Sonu Rajak ◽  
P. Parthiban ◽  
R. Dhanalakshmi
Keyword(s):  
Supply Chain ◽  
Environmental Impact ◽  
Closed Loop ◽  
Analytic Network Process ◽  
Network Design Problem ◽  
Fixed Cost ◽  
Closed Loop Supply Chain ◽  
Network Process ◽  
Milp Model ◽  
Optimum Cost

This article presents a closed-loop supply chain (CLSC) network design problem consisting of both forward and reverse material flows. Here, a four-echelon single-product system is introduced in which multiple transportation channels are considered between the nodes of each echelon. Each design is analyzed for the optimum cost, time and environmental impact which form objective functions. The problem is modeled as a tri-objective mixed integer linear programming (MILP) model. The cost objective aggregates the opening cost (fixed cost) and the variable costs in both forward and reverses material flow. The time objective considers the longest transportation time from plants to customers and reverse. Factors of environmental impact are categorized and weighed using an analytic network process (ANP) which forms the environmental objective function. A genetic algorithm (GA) has been applied as a solution methodology to solve the MILP model. Ultimately, a case problem is also used to illustrate the model developed and concluding remarks are made regarding the results.

Selection of Transportation Channels in Closed-Loop Supply Chain Using Meta-Heuristic Algorithm

2018 ◽  
Vol 11 (3) ◽  
pp. 64-86 ◽  
Author(s):  
Sonu Rajak ◽  
P. Parthiban ◽  
R. Dhanalakshmi
Keyword(s):  
Supply Chain ◽  
Environmental Impact ◽  
Closed Loop ◽  
Analytic Network Process ◽  
Network Design Problem ◽  
Mixed Integer ◽  
Fixed Cost ◽  
Closed Loop Supply Chain ◽  
Network Process ◽  
Milp Model

This article presents a closed-loop supply chain (CLSC) network design problem consisting of both forward and reverse material flows. Here, a four-echelon single-product system is introduced in which multiple transportation channels are considered between the nodes of each echelon. Each design is analyzed for the optimum cost, time and environmental impact which form objective functions. The problem is modeled as a tri-objective mixed integer linear programming (MILP) model. The cost objective aggregates the opening cost (fixed cost) and the variable costs in both forward and reverses material flow. The time objective considers the longest transportation time from plants to customers and reverse. Factors of environmental impact are categorized and weighed using an analytic network process (ANP) which forms the environmental objective function. A genetic algorithm (GA) has been applied as a solution methodology to solve the MILP model. Ultimately, a case problem is also used to illustrate the model developed and concluding remarks are made regarding the results.

scholarly journals A hybrid method to design and optimize a battery closed-loop supply chain: multi-objective approach

2021 ◽  
Author(s):  
Babak Mohamadpour Tosarkani
Keyword(s):  
Supply Chain ◽  
Closed Loop ◽  
Reverse Flow ◽  
Transportation Cost ◽  
Fuzzy Programming ◽  
Analytic Network Process ◽  
Mixed Integer ◽  
Closed Loop Supply Chain ◽  
Multi Objective ◽  
Network Process

There are a variety of prominent factors associated with total expected profit of a closed-loop supply chain (CLSC). In a forward flow, volatility in transportation cost, inventory cost, and forecasting the market’s demand are the most challenging issues for decision makers, while determining the rate of returned products and efficiency in recycling the returned products are crucial parameters to predict in reverse flow. In this thesis, it is aimed to develop and apply mixed-integer linear programming (MILP), scenario-based analysis, and fully fuzzy programming (FFP) methods to maximize the profit for a multi-echelon, multi-components, multi-product, multi-period battery CLSC in Vancouver, Canada. Furthermore, the proposed model is extended to multi-objective to consider the green factors related to plants and battery recovery centers. Fuzzy analytic network process (Fuzzy ANP) is utilized to convert the qualitative factors to the measurable parameters. Then, distance technique and ℇ-constraint method are utilized for solving the multi-objective problem.

scholarly journals A hybrid method to design and optimize a battery closed-loop supply chain: multi-objective approach

2021 ◽  
Author(s):  
Babak Mohamadpour Tosarkani
Keyword(s):  
Supply Chain ◽  
Closed Loop ◽  
Reverse Flow ◽  
Transportation Cost ◽  
Fuzzy Programming ◽  
Analytic Network Process ◽  
Mixed Integer ◽  
Closed Loop Supply Chain ◽  
Multi Objective ◽  
Network Process

There are a variety of prominent factors associated with total expected profit of a closed-loop supply chain (CLSC). In a forward flow, volatility in transportation cost, inventory cost, and forecasting the market’s demand are the most challenging issues for decision makers, while determining the rate of returned products and efficiency in recycling the returned products are crucial parameters to predict in reverse flow. In this thesis, it is aimed to develop and apply mixed-integer linear programming (MILP), scenario-based analysis, and fully fuzzy programming (FFP) methods to maximize the profit for a multi-echelon, multi-components, multi-product, multi-period battery CLSC in Vancouver, Canada. Furthermore, the proposed model is extended to multi-objective to consider the green factors related to plants and battery recovery centers. Fuzzy analytic network process (Fuzzy ANP) is utilized to convert the qualitative factors to the measurable parameters. Then, distance technique and ℇ-constraint method are utilized for solving the multi-objective problem.

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.

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