Optimization of virtual closed-loop supply chain under uncertainty: application of IoT

Kybernetes ◽  
2022 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Hanieh Shambayati ◽  
Mohsen Shafiei Nikabadi ◽  
Seyed Mohammad Ali Khatami Firouzabadi ◽  
Mohammad Rahmanimanesh ◽  
Sara Saberi

PurposeSupply chains (SCs) have been growingly virtualized in response to the market challenges and opportunities that are presented by new and cost-effective internet-based technologies today. This paper designed a virtual closed-loop supply chain (VCLSC) network based on multiperiod, multiproduct and by using the Internet of Things (IoT). The purpose of the paper is the optimization of the VCLSC network.Design/methodology/approachThe proposed model considers the maximization of profit. For this purpose, costs related to virtualization such as security, energy consumption, recall and IoT facilities along with the usual costs of the SC are considered in the model. Due to real-world demand fluctuations, in this model, demand is considered fuzzy. Finally, the problem is solved using the Grey Wolf algorithm and Firefly algorithm. A numerical example and sensitivity analysis on the main parameters of the model are used to describe the importance and applicability of the developed model.FindingsThe findings showed that the Firefly algorithm performed better and identified more profit for the SC in each period. Also, the results of the sensitivity analysis using the IoT in a VCLSC showed that the profit of the virtual supply chain (VSC) is higher compared to not using IoT due to tracking defective parts and identifying reversible products. In proposed model, chain members can help improve chain operations by tracking raw materials and products, delivering products faster and with higher quality to customers, bringing a new level of SC efficiency to industries. As a result, VSCs can be controlled, programmed and optimized remotely over the Internet based on virtual objects rather than direct observation.Originality/valueThere are limited researches on designing and optimizing the VCLSC network. This study is one of the first studies that optimize the VSC networks considering minimization of virtual costs and maximization of profits. In most researches, the theory of VSC and its advantages have been described, while in this research, mathematical optimization and modeling of the VSC have been done, and it has been tried to apply SC virtualization using the IoT. Considering virtual costs in VSC optimization is another originality of this research. Also, considering the uncertainty in the SC brings the issue closer to the real world. In this study, virtualization costs including security, recall and energy consumption in SC optimization are considered.HighlightsInvestigates the role of IoT for virtual supply chain profit optimization and mathematical optimization of virtual closed-loop supply chain (VCLSC) based on multiperiod, multiproduct with emphasis on using the IoT under uncertainty.Considering the most important costs of virtualization of supply chain include: cost of IoT information security, cost of IoT energy consumption, cost of recall the production department, cost of IoT facilities.Selection of the optimal suppliers in each period and determination of the price of each returned product in virtual supply chain.Solving and validating the proposed model with two meta-heuristic algorithms (the Grey Wolf algorithm and Firefly algorithm).

2020 ◽  
Vol 15 (4) ◽  
pp. 1613-1653
Author(s):  
Jaber Valizadeh ◽  
Ehsan Sadeh ◽  
Zainolabedin Amini Sabegh ◽  
Ashkan Hafezalkotob

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.


2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Saeid Jafarzadeh Ghoushchi ◽  
Iman Hushyar ◽  
Kamyar Sabri-Laghaie

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.


2019 ◽  
Vol 17 (1) ◽  
pp. 131-159
Author(s):  
S. Umar Sherif ◽  
P. Sasikumar ◽  
P. Asokan ◽  
J. Jerald

Purpose Due to the economic benefits and environmental awareness, most of the battery manufacturing industries in India are interested to redesign their existing supply chain network or to incorporate the effective closed loop supply chain network (CLSCN). The purpose of this paper is to develop CLSCN model with eco-friendly distribution network and also enhance recycling to utilize recycled lead for new battery production. The existing CLSCN model of a battery manufacturing industry considered for case study is customized for attaining economic benefit and environmental safety. Hence, single objective, multi-echelon, multi-period and multi-product CLSCN model with centralized depots (CD) is developed in this work to maximize the profit and reduce the emission of CO2 in transportation. Design/methodology/approach The proposed CD has the facility to store new batteries (NB), scrap batteries (SB) and lead ingot. The objective of the proposed research work is to identify potential location of CD using K-means clustering algorithm, to allocate facilities with CD using multi-facility allocation (MFA) algorithm and to minimize overall travel distance by allowing bidirectional flow of materials and products between facilities. The proposed eco-friendly CLSCN-CD model is solved using GAMS 23.5 for optimal solutions. Findings The performance of the proposed model is validated by comparing with existing model. The evaluation reveals that the proposed model is better than the existing model. The sensitivity analysis is demonstrated with different rate of return of SB, different proportion of recycled lead and different type of vehicles, which will help the management to take appropriate decision in the context of cost savings. Originality/value This research work has proposed single objective, multi echelon, multi period and multi product CLSCN-CD model in the battery manufacturing industry to maximize the profit and reduce the CO2 emission in transportation, by enhancing the bidirectional flow of materials/products between facilities of entire model.


2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Saman Esmaeilian ◽  
Dariush Mohamadi ◽  
Majid Esmaelian ◽  
Mostafa Ebrahimpour

Purpose This paper aims to minimize the total carbon emissions and costs and also maximize the total social benefits. Design/methodology/approach The present study develops a mathematical model for a closed-loop supply chain network of perishable products so that considers the vital aspects of sustainability across the life cycle of the supply chain network. To evaluate carbon emissions, two different regulating policies are studied. Findings According to the obtained results, increasing the lifetime of the perishable products improves the incorporated objective function (IOF) in both the carbon cap-and-trade model and the model with a strict cap on carbon emission while the solving time increases in both models. Moreover, the computational efficiency of the carbon cap-and-trade model is higher than that of the model with a strict cap, but its value of the IOF is worse. Results indicate that efficient policies for carbon management will support planners to achieve sustainability in a cost-effectively manner. Originality/value This research proposes a mathematical model for the sustainable closed-loop supply chain of perishable products that applies the significant aspects of sustainability across the life cycle of the supply chain network. Regional economic value, regional development, unemployment rate and the number of job opportunities created in the regions are considered as the social dimension.


2012 ◽  
Vol 190-191 ◽  
pp. 218-221 ◽  
Author(s):  
Yu Juan Chen ◽  
Dong Bo Liu ◽  
Hong Wei Mao ◽  
Zi Qiang Zhang

This paper addresses an integrated uncertain programming model for a closed-loop supply chain with manufacturing/remanufacturing hybrid system. The hybrid system is studied under the grey fuzzy uncertainty and grey uncertainty. The hybrid intelligent optimization algorithm integrating the grey fuzzy simulation, neural network and genetic algorithm can optimize the uncertain model. One numerical example is given to illustrate the effectiveness of the proposed model and algorithm.


2018 ◽  
Vol 118 (2) ◽  
pp. 480-498 ◽  
Author(s):  
Yacan Wang ◽  
Benjamin T. Hazen ◽  
Diane A. Mollenkopf

Purpose The success of closed loop supply chains is contingent upon consumer acceptance of remanufactured products, yet little is known about how consumers value such products. The purpose of this paper is to provide theoretical grounding for understanding consumers’ value perceptions as related to remanufactured products. Design/methodology/approach Diffusion of innovation theory and customer perceived value literature help form the theoretical model, which is tested empirically using survey data of consumers. Structural equation modeling was employed to test the hypotheses. Findings Perceived value of remanufactured products is measured as a function of perceived benefits (environmental benefits; price advantage) and perceived sacrifices (perceived quality; perceived risk), all of which are shown to impact perceived value. Additionally, perceived risk is found to partially mediate the relationship between perceived quality and perceived value. Originality/value This research makes two significant contributions. First, mid-range theory that is contextualized to the closed loop supply chain is developed to aid researchers and practitioners in better understanding the consumer’s role in the closed loop supply chain, as related to the acceptance of remanufactured products. Second, consumer acceptance of remanufactured products represents a form of supply chain demand risk that has previously been unrecognized. The results provide a foundation for incorporating this type of demand risk in to future research efforts.


2013 ◽  
Vol 136 (2) ◽  
Author(s):  
Wu-Hsun Chung ◽  
Gül E. Okudan Kremer ◽  
Richard A. Wysk

As environmental concerns have grown in recent years, the interest in product design for the life cycle (DFLC) has exhibited a parallel surge. Modular design has the potential to bring life cycle considerations into the product architecture decision-making process, yet most current modular design methods lack the capability for assessing module life cycle consequences in a supply chain. This paper proposes a method for product designers, called the architecture and supply chain evaluation method (ASCEM), to find a product modular architecture with both low life cycle costs and low energy consumption at the early design stages. ASCEM expands the assessment scope from the product's architecture to its supply chain network. This work analyzes the life cycle costs (LCCs) and energy consumption (LCEC) of two products designated within the European Union's directive on waste of electric and electronic equipment (WEEE) within a closed-loop supply chain to identify the most beneficial modular structure. In addition, data on 27 theoretical cases representing various products are analyzed to show the broader applicability of the proposed methodology. Our analysis shows that ASCEM can efficiently identify a good-quality modular structure having low LCC and LCEC in a closed-loop supply chain for both the two tested products and the hypothetical cases.


2021 ◽  
Vol 13 (12) ◽  
pp. 6663
Author(s):  
Muhammad Salman Shabbir ◽  
Ahmed Faisal Siddiqi ◽  
Lis M. Yapanto ◽  
Evgeny E. Tonkov ◽  
Andrey Leonidovich Poltarykhin ◽  
...  

In today’s competitive environment, organizations, in addition to trying to improve their production conditions, have a special focus on their supply chain components. Cooperation between supply chain members always reduces unforeseen costs and speeds up the response to customer demand. In the new situation, according to the category of return products and their reprocessing, supply chains have found a closed-loop structure. In this research, the aim was to design a closed-loop supply chain in competitive conditions. For this purpose, the key decisions of this chain included locating retail centers, adjusting the inventory of chain members, and selling prices of final products, optimally determined. For this purpose, a nonlinear integer mathematical model is presented. One of the most important innovations of this research was considering the variable value for return products. Then, in order to solve the proposed model, a whale optimization algorithm was developed. Numerical results from the sample examples showed that the whale algorithm had a very good performance in terms of response quality and speed-of-action in finding the optimal solution to this problem.


Kybernetes ◽  
2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Na Wang ◽  
Yulin Zhang ◽  
Jing Li

PurposeOutsourcing remanufacturing is a major form of remanufacturing, and emission reduction is an important part of a manufacturer's production. This paper aims to investigate carbon emission reduction strategies in a closed-loop supply chain (CLSC) with outsourcing remanufacturing and design a contract to coordinate the CLSC.Design/methodology/approachThe authors establish two-period game models between an original equipment manufacturer (OEM) and third-party remanufacturer (TPR) in different scenarios, including decentralized decision, centralized decision and coordinated decision. Furthermore, the authors study the optimal decisions by maximizing the profit model. The authors also investigate the impact of a carbon tax and emission reduction on the optimal decisions through comparative analysis.FindingsEmission reduction increases the quantity of new products and the OEM's profit. However, emission reduction decreases the outsourcing fee, which is not conducive to remanufacturing; thus, the TPR's profit does not necessarily increase. Compared with a decentralized scenario, the output of remanufactured products and the total profit increase. When the acceptance level of remanufactured products is high enough or when emissions from remanufacturing are low enough, the total carbon emissions are reduced in the centralized scenario. For the coordination of the CLSC, the OEM needs to increase the outsourcing fee and the TPR needs to share part of the emission reduction costs.Research limitations/implicationsThe TPR can choose three different remanufacturing strategies, namely, no remanufacturing, partial remanufacturing or full remanufacturing. For the majority of firms, it is difficult to remanufacture all used products. Therefore, the analysis is based only on partial remanufacturing.Practical implicationsThe results provide insights for remanufacturing and emission reduction decisions, as well as a decision basis for the cooperation between the OEM and TPR.Originality/valueThe authors combine the OEM's carbon emission reduction with outsourcing remanufacturing, and investigate the impact of technological spillover on the TPR's profit.


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