scholarly journals Designing a Sustainable Green Closed-Loop Supply Chain under Uncertainty and Various Capacity Levels

Logistics ◽  
2021 ◽  
Vol 5 (2) ◽  
pp. 20
Author(s):  
Mohsen Tehrani ◽  
Surendra M. Gupta
Keyword(s):  
Supply Chain ◽  
Closed Loop ◽  
Production Costs ◽  
Mixed Integer ◽  
Risk Level ◽  
Programming Approach ◽  
Supply Chain Network ◽  
Closed Loop Supply Chain ◽  
Tire Industry ◽  
Hybrid Uncertainty

The ever-increasing concerns of the growth in the volume of waste tires and new strict government legislations to reduce the environmental impact of the end-of-life (EOL) tires have increased interest among companies to design a sustainable and efficient closed-loop supply-chain (CLSC) network. In the real world, the CLSC network design is subject to a variety of uncertainties, such as random and fuzzy (epistemic) uncertainties. Designing a reliable and environmentally cautious CLSC with consideration of risks and the uncertainty of the parameters in the network is necessary for a successful supply-chain network. This study proposes a sustainable and environmentally cautious closed-loop supply-chain network for the tire industry, by considering several recovery options, including retreading, recycling, and energy recovery. This study aims to design and develop a robust multi-objective, multi-product, multi-echelon, multi-cycle, multi-capacity, green closed-loop supply-chain network under hybrid uncertainty. There are two types of uncertainties associated with the parameters in the network. There is an uncertainty associated with the demand, which is expressed in some future scenarios according to the probability of their occurrences, as well as fuzzy-based uncertainty associated with return rates, retreading rates, recycling rates, procurement, and production costs, which are expressed with possibilistic distributions. In order to deal with this hybrid uncertainty, a robust fuzzy stochastic programming approach has been proposed, and the proposed mixed integer programming model is applied to a case study in the tire industry to validate the model. The result indicates the applicability of the proposed model and its efficiency to control the hybrid uncertainties and the risk level in the network.

scholarly journals A multi-objective optimization of closed-loop supply chain problem with vehicle routing

2021 ◽  
Vol 6 (2) ◽  
pp. 121-130
Author(s):  
Shahul Hamid Khan ◽  
Vivek Kumar Chouhan ◽  
Santhosh Srinivasan
Keyword(s):  
Supply Chain ◽  
Closed Loop ◽  
Consumer Products ◽  
Product Recovery ◽  
Business Strategies ◽  
Mixed Integer ◽  
Programming Approach ◽  
Closed Loop Supply Chain ◽  
Competitive Edge ◽  
Chain Problem

Product recovery has become significant business strategies to increase a competitive edge in business and also in the society. Parts from discarded products due to rapid advancement and post-consumer products before & after end-of-life (EOL) are recovered to reduce landfill waste and to have become a part of circular economy. Product recovery is made possible with the help of Closed-loop supply chain (CLSC). This paper concentrates on multi-period, multi-product, and multi-echelon Closed Loop Green Supply Chain (CLGSC) network. A bi-objective (cost and emission) Mixed Integer Linear Programming (MILP) model has been formulated for the network and has been optimized using Goal Programming approach and Genetic Algorithm. Results are discussed for providing some managerial insights of the model.

scholarly journals Economic pricing of complex products in a competitive closed-loop supply chain network under uncertainty: A case study of CoPS industry

2021 ◽  
Author(s):  
Omid - Solgi ◽  
Alireza - Taromi ◽  
jafar ghidar kheljani ◽  
Ehsan - Dehghani
Keyword(s):  
Mathematical Model ◽  
Supply Chain ◽  
Closed Loop ◽  
Optimal Solution ◽  
Production Costs ◽  
Supply Chain Network ◽  
Closed Loop Supply Chain ◽  
Complex Products ◽  
Complex Product Systems

The development of technology, the globalization of the economy, and the unpredictable behavior of customers have led to a dynamic and competitive environment in the Complex Product Systems (CoPS) market. Besides, CoPS economic pricing is one of the key factors that significantly reduces production costs of Complex products and systems  ​​and increases competitiveness . In this regard, this paper develops a hybrid data envelopment analysis (DEA) fuzzy mathematical model for economic pricing of CoPS in a competitive closed-loop supply chain network under uncertainty, which leads to productivity and reducing the costs. To achieve the aim of this study, at first, different CoPS providers were evaluated using DEA based on a set of economic, technical, and geographical criteria . The advantage of this evaluation was choosing the right providers, eliminating inappropriate providers, and reducing complexity as one of the fundamental problems in mathematical models. Next, we maximize the benefit of the supply chain using the mathematical model. The objective of the proposed model is to identify strategic and tactical decisions at the same time to provide a fully optimal solution to the model. Furthermore, the presented robust model is capable of providing a stable structure under different uncertainties. This leads to minimizing the purchasing cost of CoPS manufacturers. Eventually, to evaluate the effectiveness and usefulness of the proposed approach, a case study was used to derive important managerial results .

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.

scholarly journals A hybrid NSGA-II algorithm for the closed-loop supply chain network design in e-commerce  

2021 ◽  
Author(s):  
Shayan Shafiee Moghadam ◽  
Amir Aghsami ◽  
Masoud Rabbani
Keyword(s):  
Supply Chain ◽  
Closed Loop ◽  
Programming Model ◽  
Mixed Integer ◽  
Modern World ◽  
Supply Chain Network ◽  
Nsga Ii ◽  
Closed Loop Supply Chain ◽  
Proposed Model ◽  
Nonlinear Programming Model

Designing the supply chain network is one of the significant areas in e-commerce business management. This concept plays a crucial role in e-commerce systems. For example, location-inventory-pricing-routing of an e-commerce supply chain is considered a crucial issue in this field. This field established many severe challenges in the modern world, like maintaining the supply chain for returned items, preserving customers' trust and satisfaction, and developing an applicable supply chain with cost considerations. The research proposes a multi-objective mixed integer nonlinear programming model to design a closed-loop supply chain network based on the e-commerce context. The proposed model incorporates two objectives that optimize the business's total profits and the customers' satisfaction. Then, numerous numerical examples are generated and solved using the epsilon constraint method in GAMS optimization software. The validation of the given model has been tested for the large problems via a hybrid two-level non-dominated sort genetic algorithm. Finally, some sensitivity analysis has been performed to provide some managerial insights.

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