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 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 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.

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.

Robust optimization model for sustainable supply chain for production and distribution of polyethylene pipe

2020 ◽  
Vol 15 (4) ◽  
pp. 1613-1653
Author(s):  
Jaber Valizadeh ◽  
Ehsan Sadeh ◽  
Zainolabedin Amini Sabegh ◽  
Ashkan Hafezalkotob
Keyword(s):  
Genetic Algorithm ◽  
Supply Chain ◽  
Environmental Impacts ◽  
Closed Loop ◽  
Optimal Location ◽  
Computational Time ◽  
Closed Loop Supply Chain ◽  
Content Type ◽  
Proposed Model ◽  
Production And Distribution

Purpose In this study, the authors consider the key decisions in the design of the green closed-loop supply chain (CSLC) network. These decisions include considering the optimal location of suppliers, production facilities, distribution, customers, recycling centers and disposal of non-recyclable goods. In the proposed model, the level of technology used in recycling and production centers is taken into account. Moreover, in this paper is the environmental impacts of production and distribution of products based on the eco-indicator 99 are considered. Design/methodology/approach In this study, the author consider the key decisions in the design of the green CLSC network. These decisions include considering the optimal location of suppliers, production facilities, distribution, customers, recycling centers and disposal of non-recyclable goods. In the proposed model, the level of technology used in recycling and production centers is taken into account. Moreover, the environmental impacts of production and distribution of products based on the eco-indicator 99 are considered. Findings The results indicate that the results obtained from the colonial competition algorithm have higher quality than the genetic algorithm. This quality of results includes relative percentage deviation and computational time of the algorithm and it is shown that the computational time of the colonial competition algorithm is significantly lower than the computational time of the genetic algorithm. Furthermore, the limit test and sensitivity analysis results show that the proposed model has sufficient accuracy. Originality/value Solid modeling of the green supply chain of the closed loop using the solid optimized method by Bertsimas and Sim. Development of models that considered environmental impacts to the closed loop supply chain. Considering the impact of the technology type in the manufacture of products and the recycling of waste that will reduce emissions of environmental pollutants. Another innovation of the model is the multi-cycle modeling of the closed loop of supply chain by considering the uncertainty and the fixed and variable cost of transport.

Closed supply network modelling for end-of-life ship remanufacturing

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Prem Chhetri ◽  
Mahsa Javan Nikkhah ◽  
Hamed Soleimani ◽  
Shahrooz Shahparvari ◽  
Ashkan Shamlou
Keyword(s):  
Supply Chain ◽  
End Of Life ◽  
Closed Loop ◽  
Payback Period ◽  
Mixed Integer ◽  
Supply Chain Network ◽  
Supply Network ◽  
Closed Loop Supply Chain ◽  
Content Type ◽  
Milp Model

PurposeThis paper designs an optimal closed-loop supply chain network with an integrated forward and reverse logistics to examine the possibility of remanufacturing end-of-life (EoL) ships.Design/methodology/approachExplanatory variables are used to estimate the number of EoL ships available in a closed-loop supply chain network. The estimated number of EoL ships is used as an input in the model and then it is solved by a mixed-integer linear programming (MILP) model of the closed-loop supply chain network to minimise the total logistic costs. A discounted payback period formula is developed to calculate the length of time to recoup an investment based on the investment's discounted cash flows. Existing ship wrecking industry clusters in the Western region of India are used as the case study to apply the proposed model.FindingsThe MILP model has optimised the total logistics costs of the closed-loop supply network and ascertained the optimal number and location of remanufacturing for building EoL ships. The capital and variable costs required for establishing and operating remanufacturing centres are computed. To remanufacture 30 ships a year, the discounted payback period of this project is estimated to be less than two years.Practical implicationsShip manufacturing businesses are yet to re-manufacture EoL ships, given high upfront capital expenditure and operational challenges. This study provides management insights into the costs and benefits of EoL ship remanufacturing; thus, informing the decision-makers to make strategic operational decisions.Originality/valueThe design of an optimal close loop supply chain network coupled with a Bayesian network approach and discounted payback period formula for the collection and remanufacturing of EoL ships provides a new integrated perspective to ship manufacturing.

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