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 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 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.

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 Dual-Channel Global Closed-Loop Supply Chain Network Optimization Based on Random Demand and Recovery Rate

2020 ◽  
Vol 17 (23) ◽  
pp. 8768
Author(s):  
Aijun Liu ◽  
Yan Zhang ◽  
Senhao Luo ◽  
Jie Miao
Keyword(s):  
Supply Chain ◽  
Closed Loop ◽  
Net Present Value ◽  
Programming Model ◽  
Social Performance ◽  
Strategic Decision ◽  
Mixed Integer ◽  
Closed Loop Supply Chain ◽  
Multi Objective ◽  
Product Demand

In the process of globalization, customer demand is usually difficult to predict, and product recycling is generally difficult to achieve accurately. It is also urgent to deal with increased inventory while avoiding shortages, with the purpose of reducing supply chain risks. This study analyzes the integrated supply chain decision-making problem in the random product demand and return environment. It proposes a multi-objective optimization model, which is an effective tool to solve the design and planning problems of the global closed-loop supply chain. It consists of a multi-period, single-product and multi-objective mixed integer linear programming model, which can solve some strategic decision problems, including the network structure, entity capacities, flow of products and components, and collection levels, as well as the inventory levels. From the perspective of economic, environmental and social benefits, three objective functions are defined, including maximizing the net present value (NPV) of the system, minimizing the total CO2e emissions of supply chain activities, and maximizing social sustainability indicators. Finally, a numerical example is provided to verify the advantages of this model, and sensitivity analysis results are provided. The results show that changes in product demand and return rate will have a great impact on economic and social performance.

scholarly journals A multi-objective optimal decision model for a green closed-loop supply chain under uncertainty: A real industrial case study

2021 ◽  
Vol 16 (2) ◽  
pp. 161-172
Author(s):  
I.W. Fang ◽  
W.-T. Lin
Keyword(s):  
Supply Chain ◽  
Closed Loop ◽  
Resource Scarcity ◽  
Mixed Integer ◽  
Optimal Decision ◽  
Quality Level ◽  
Chain Model ◽  
Closed Loop Supply Chain ◽  
Multi Objective ◽  
Proposed Model

Green closed-loop supply chain management is an important topic for business operations today because of increasing resource scarcity and environmental issues. Companies not only have to meet environmental regulations, but also must ensure high quality supply chain operation as a means to secure competitive advantages and increase profits. This study proposes a multi-objective mixed integer programming model for an integrated green closed-loop supply chain network designed to maximize profit, amicable production level (environmentally friendly materials and clean technology usage), and quality level. A scenario-based robust optimization method is used to deal with uncertain parameters such as the demand of new products, the return rates of returned products and the sale prices of remanufactured products. The proposed model is applied to a real industry case example of a manufacturing company to illustrate the applicability of the proposed model. The result shows a robust optimal resource allocation solution that considers multiple scenarios. This study can be a reference for closed-loop supply chain related academic research and also can be used to guide the development of a green closed-loop supply chain model for better decision making.

A multi-objective mixed-integer linear model for sustainable fruit closed-loop supply chain network

2020 ◽  
Vol 31 (5) ◽  
pp. 1351-1373
Author(s):  
Younis Jabarzadeh ◽  
Hossein Reyhani Yamchi ◽  
Vikas Kumar ◽  
Nader Ghaffarinasab
Keyword(s):  
Supply Chain ◽  
Closed Loop ◽  
Environmental Indicators ◽  
Mixed Integer ◽  
Computational Time ◽  
Distribution Centers ◽  
Closed Loop Supply Chain ◽  
Content Type ◽  
Multi Objective ◽  
Lp Metric

PurposeThis paper aims to present a closed-loop supply chain (CLSC) optimization problem for a perishable agricultural product to achieve three pillars of sustainability, including minimizing total network costs and carbon dioxide emissions from different network activities and maximizing responsiveness to demands simultaneously.Design/methodology/approachThe research problem is formulated as a multi-objective mixed-integer linear programming model, and classical approaches, including the LP-Metric and weighted Tchebycheff method, have been applied to solve the optimization model. A set of test problems has been proposed to validate the model, and the results are presented.FindingsComputational time to find Pareto optimal solutions by using the weighted Tchebycheff method was twice as much as that of the LP-Metric method. Also, the result of the study is a mathematical model that can be applied to other products that are close to the fruit, such as vegetables.Research limitations/implicationsThe present study is limited to fruits supply chains and the inventory is considered at the distribution centers only. The study also considers only one type of transport.Practical implicationsThe paper can assist supply chain managers to define strategies to achieve a sustainable CLSC network configuration for the fruits.Originality/valueThis study is one of the early studies to consider environmental indicators in fruits supply chain design along with two other indicators of sustainability, namely, economic and social indicators. Therefore, this can help supply chain managers to achieve sustainability by optimizing location decisions, inventory quantities and flow between facilities.

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.

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