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.

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 fuzzy approach to multi-objective mixed integer linear programming model for multi-echelon closed-loop supply chain with multi-product multi-time-period

2020 ◽  
Vol 30 (1) ◽  
Author(s):  
Sema Akin Bas ◽  
Beyza Ahlatcioglu Ozkok
Keyword(s):  
Linear Programming ◽  
Supply Chain ◽  
Integer Linear Programming ◽  
Mixed Integer Linear Programming ◽  
Closed Loop ◽  
Mixed Integer ◽  
Fuzzy Approach ◽  
Closed Loop Supply Chain ◽  
Multi Objective ◽  
Time Period

By the green point of view, supply chain management (SCM), which contains supplier and location selection, production, distribution, and inventory decisions, is an important subject being examined in recent years by both practitioners and academicians. In this paper, the closed-loop supply chain (CLSC) network that can be mutually agreed by meeting at the level of common satisfaction of conflicting objectives is designed. We construct a multi-objective mixed-integer linear programming (MOMILP) model that allows decision-makers to more effectively manage firms’ closed-loop green supply chain (SC). An ecological perspective is brought by carrying out the recycling, remanufacturing and destruction to SCM in our proposed model. Maximize the rating of the regions in which they are located, minimize total cost and carbon footprint are considered as the objectives of the model. By constructing our model, the focus of customer satisfaction is met, as well as the production, location of facilities and order allocation are decided, and we also carry out the inventory control of warehouses. In our multi-product multi-component multi-time-period model, the solution is obtained with a fuzzy approach by using the min operator of Zimmermann. To illustrate the model, we provide a practical case study, and an optimal result containing a preferable level of satisfaction to the decision-maker is obtained.

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.

scholarly journals The effects of different kinds of returns on an integrated chance-constrained stochastic mobile phone closed-loop supply chain configuration and supplier selection

2021 ◽  
Author(s):  
Shahrzad Ahmadi Kermanshah
Keyword(s):  
Supply Chain ◽  
Mobile Phone ◽  
Supplier Selection ◽  
Closed Loop ◽  
Stochastic Demand ◽  
Mixed Integer ◽  
Chance Constraint ◽  
Distance Method ◽  
Closed Loop Supply Chain ◽  
Multi Objective

One of the important concerns in the world is E-waste. Ending up e-waste in the landfill and inappropriate disposing of it are hazardous to the environment. The goal of this research is to design and optimize a multi-period, multi-product, multi-echelon, and multi-customer Closed-Loop Supply Chain (CLSC) network for a mobile phone network considering different types of product returns. Commercial, end of life, and end-of-use returns are well-known in practice. In this research, a multi-objective mixed-integer linear programming formulation with stochastic demand and return is proposed to maximize the total profit in the mobile phone CLSC network, alongside maximizing the weights of eligible suppliers which are estimated based on a fuzzy method for efficient supplier selection and order allocation. Chance-constraint programming is applied in order to deal with the stochastic demand and return. Moreover, distance method and εε-constraint technique are employed to solve the proposed multi-objective problem. The application of the proposed mathematical model is illustrated in Toronto, Canada using real maps.

scholarly journals MULTI-LEVEL OPTIMIZATION OF AN AUTOMOTIVE CLOSED-LOOP SUPPLY CHAIN NETWORK WITH INTERACTIVE FUZZY PROGRAMMING APPROACHES

2018 ◽  
Vol 24 (3) ◽  
pp. 1004-1028 ◽  
Author(s):  
Abdullah YILDIZBAŞI ◽  
Ahmet ÇALIK ◽  
Turan PAKSOY ◽  
Reza ZANJİRANİ FARAHANİ ◽  
Gerhard-Wilhelm WEBER
Keyword(s):  
Supply Chain ◽  
Automotive Industry ◽  
Closed Loop ◽  
Fuzzy Programming ◽  
Decision Makers ◽  
Mixed Integer ◽  
Closed Loop Supply Chain ◽  
Trade Offs ◽  
End Products ◽  
Multi Level

Closed-Loop Supply Chain (CLSC) management has attained appreciable attention over the last few years. CLSC management allows companies to manage their recovery and recycling activities of end products. Due to the latest developments in the world, producers are responsible for the collection, refurbishing, repairing and disassembly of end products at the end of their lives. This paper develops a mixed-integer CLSC model that is inspired by the automotive industry. In this model, we consider three Decision Makers (DM): Plant, Dismantler Center and Customer. Each DM has individual objectives and is responsible for only its own objective function under same constraints. In order to tackle the trade-offs among the objectives, we used four different Interac-tive Fuzzy Programming (IFP) approaches. The applications of the model and solution techniques are investigated in conjectural data. The paper ends with a conclusion and a call for future studies.

Multi-objective robust optimization for multi-stage-multi-product agile closed-loop supply chain under uncertainty in the context of circular economy

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Saeid Jafarzadeh Ghoushchi ◽  
Iman Hushyar ◽  
Kamyar Sabri-Laghaie
Keyword(s):  
Supply Chain ◽  
Robust Optimization ◽  
Circular Economy ◽  
Closed Loop ◽  
Mixed Integer ◽  
Closed Loop Supply Chain ◽  
Content Type ◽  
Multi Objective ◽  
Multi Stage ◽  
Proposed Model

PurposeA circular economy (CE) is an economic system that tries to eliminate waste and continually use resources. Due to growing environmental concerns, supply chain (SC) design should be based on the CE considerations. In addition, responding and satisfying customers are the challenges managers constantly encounter. This study aims to improve the design of an agile closed-loop supply chain (CLSC) from the CE point of view.Design/methodology/approachIn this research, a new multi-stage, multi-product and multi-period design of a CLSC network under uncertainty is proposed that aligns with the goals of CE and SC participants. Recycling of goods is an important part of the CLSC. Therefore, a multi-objective mixed-integer linear programming model (MILP) is proposed to formulate the problem. Besides, a robust counterpart of multi-objective MILP is offered based on robust optimization to cope with the uncertainty of parameters. Finally, the proposed model is solved using the e-constraint method.FindingsThe proposed model aims to provide the strategic choice of economic order to the suppliers and third-party logistic companies. The present study, which is carried out using a numerical example and sensitivity analysis, provides a robust model and solution methodology that are effective and applicable in CE-related problems.Practical implicationsThis study shows how all upstream and downstream units of the SC network must work integrated to meet customer needs considering the CE context.Originality/valueThe main goal of the CE is to optimize resources, reduce the use of raw materials, and revitalize waste by recycling. In this study, a comprehensive model that can consider both SC design and CE necessities is developed that considers all SC participants.

scholarly journals A Hybrid Approach to Solve a Model of Closed-Loop Supply Chain

2015 ◽  
Vol 2015 ◽  
pp. 1-18 ◽  
Author(s):  
Nafiseh Tokhmehchi ◽  
Ahmad Makui ◽  
Soheil Sadi-Nezhad
Keyword(s):  
Supply Chain ◽  
Closed Loop ◽  
Reverse Flow ◽  
Hybrid Approach ◽  
The Other ◽  
Mixed Integer ◽  
Closed Loop Supply Chain ◽  
Total Cost ◽  
Large Size ◽  
Hybrid Forms

This paper investigates a closed-loop supply chain network, including plants, demand centers, as well as collection centers, and disposal centers. In forward flow, the products are directly sent to demand centers, after being produced by plants, but in the reverse flow, reused products are returned to collection centers and, after investigating, are partly sent to disposal centers and the other part is resent to plants for remanufacturing. The proposed mathematical model is based on mixed-integer programming and helps minimizing the total cost. Total costs include the expenditure of establishing new centers, producing new products, cargo transport in the network, and disposal. The model aims to answer these two questions. (1) What number and in which places the plants, collection centers, and disposal centers will be constructed. (2) What amount of products will be flowing in each segment of the chain, in order to minimize the total cost. Four types of tuned metaheuristic algorithms were used, which are hybrid forms of genetic and firefly algorithms. Finally an adequate number of instances are generated to analyse the behavior of proposed algorithms. Computational results reveal that iterative sequentialization hybrid provides better solution compared with the other approaches in large size.

Sustainable Design of a Multi-Echelon Closed Loop Supply Chain under Uncertainty for Durable Products

2021 ◽  
Vol 13 (19) ◽  
pp. 11126
Author(s):  
Abbas Al-Refaie ◽  
Yasmeen Jarrar ◽  
Natalija Lepkova
Keyword(s):  
Supply Chain ◽  
Stochastic Model ◽  
Environmental Sustainability ◽  
Closed Loop ◽  
Transportation Cost ◽  
Return Rate ◽  
Raw Material ◽  
Mixed Integer ◽  
Closed Loop Supply Chain ◽  
Durable Products

The increased awareness of environmental sustainability has led to increasing attention to closed loop supply chains (CLSC). The main objective of the CLSC is to capture values from end-of-life (EOL) products in a way that ensures a business to be economically and environmentally sustainable. The challenge is the complexity that occurrs due to closing the loop. At the same time, considering stochastic variables will increase the realism of the obtained results as well as the complexity of the model. This study aims to design a CLSC for durable products using a multistage stochastic model in mixed-integer linear programming (MILP) while considering uncertainty in demand, return rate, and return quality. Demand was described by a normal distribution whereas return rate and return quality were represented by a set of discrete possible outcomes with a specific probability. The objective function was to maximize the profit in a multi-period and multi-echelon CLSC. The multistage stochastic model was tested on a real case study at an air-conditioning company. The computational results identified which facilities should be opened in the reversed loop to optimize profit. The results showed that the CLSC resulted in a reduction in purchasing costs by 52%, an annual savings of 831,150 USD, and extra annual revenue of 5459 USD from selling raw material at a material market. However, the transportation cost increased by an additional annual cost of 6457 USD, and the various recovery processes costs were annually about 152,897 USD. By running the model for nine years, the breakeven point will be after three years of establishing the CLSC and after the annual profit increases by 1.92%. In conclusion, the results of this research provide valuable analysis that may support decision-makers in supply chain planning regarding the feasibility of converting the forward chain to closed loop supply chain for durable products.

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