A closed-loop supply chain configuration considering environmental impacts: a self-adaptive NSGA-II algorithm

Babaeinesami, Abdollah; Tohidi, Hamid; Ghasemi, Peiman; Goodarzian, Fariba; Tirkolaee, Erfan Babaee

doi:10.1007/s10489-021-02944-9

Cited by 52 publications

(35 citation statements)

References 45 publications

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“…Later, Sazvar et al [44] exhibited a new replenishment policy in a coordinated supply chain by developing a linear multi-objective mathematical model. Babaeinesami et al [4] and Alinezhad et al [3] developed a closedloop supply chain problem by considering three, objective functions; one is maximization of the total profit, second is the minimization of total carbon footprint cost and third is the minimization of the maximum demand back log rate. To solve multi-objective optimization problems, various methods such as multi-objective grey wolf optimizer and multi-objective water cycle algorithm (Khalilpourazari et al [20]) have been proposed.…”

Section: Sustainable and Multi-objective Inventory Modelmentioning

confidence: 99%

Impacts of green and preservation technology investments on a sustainable EPQ model during COVID-19 pandemic

Barman

Pervin²,

Roy

2022

RAIRO-Oper. Res.

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Carbon and Sulfur dioxides emissions are the key issues of global warming that affects on human health. Emissions cap- and -trade policy is a key mechanism implemented in several countries to reduce the emissions. Nowadays, public gathering is restricted due to the pandemic situation caused by COVID-19. As a result, people are facing huge problems in their regular activities and lifestyle. During the lockdown periods, demands for few merchandises decrease and the deterioration rate increases. Moreover, because of the unavailability of raw materials and labours during the lockdown, shortages occur at the manufacturing company. Keeping these problems in mind, a multi-objective sustainable economic production quantity model is proposed with partially back-ordering shortages, in which the effects of sustainability are investigated. To handle the demand fluctuation throughout the current pandemic, emergency level dependent demand rate is assumed. To reduce greenhouse gases emissions and deterioration rate, investments in green technology and preservation technology efforts are used. The objectives of this study are to maximize the manufacturer’s profit and minimize the greenhouse gases emissions for producing green products. The multi-objective model is solved by utilizing the fuzzy goal programming approach. The mathematical model is illustrated by four numerical examples. The main finding of the work is that under both green and preservation technologies investments, a sustainable model with partially back-ordering shortages and lockdown level dependent demand rate decreases justifiable greenhouse gases emissions and increases the product’s greening level. The results indicate that the system profit is increased by 16.1% by investing in both preservation and green technology. Furthermore, a sensitivity analysis is performed along with some managerial insights for practitioners. Finally, the paper is ended with conclusions and future research tips.

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Section: Sustainable and Multi-objective Inventory Modelmentioning

confidence: 99%

Impacts of green and preservation technology investments on a sustainable EPQ model during COVID-19 pandemic

Barman

Pervin²,

Roy

2022

RAIRO-Oper. Res.

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“…Therefore, establishing more distribution centers will increase operating costs and expand coverage are. Babaeinesami, et al (2022) In his research, the question concerns a closed-loop supply chain (CLSC) network design considering suppliers, assembly centers, retailers, customers, collection centers, refurbishing centers, disassembly centers and disposal centers. It aims to design a distribution network based on customers' needs in order to simultaneously minimize the total cost and total CO2 emission.…”

Section: Introductionmentioning

confidence: 99%

Presenting an Agile Supply Chain Mathematical Model for Covid 19 (Corona) Drugs Using Metaheuristic Algorithms (Case Study: Pharmaceutical Industry)

Shayannia

2022

Preprint

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This article focuses on the strategic issue of an agile supply chain. Different goals are considered in supply chain design. Today, the concept of sustainability in supply chains plays an important role in goal setting. In general, sustainability leads to less economic, social, and environmental risks, and attention to this type of sustainability covers many criteria in the literature. Therefore, in this study, optimization of the stability of a supply chain network has been considered. In addition, a lesser-known aspect of sustainability, the political aspect, has been added to the previous aspects. This paper assumes four levels, namely supplier, wholesaler, retailer, and customer. An optimal network structure is designed to consider economic, social and environmental sustainability and the new measure of political sustainability. The design of this supply chain is done by defining a mathematical model that has several objective functions, including economic, political, and environmental goals. These objective functions select the relationships and links between the levels in a supply chain network. For this purpose, a directional graph corresponding to a supply chain is designed. Then, with the help of an ideal multi-objective planning problem, an optimal configuration is obtained, which is a subgraph of the main network graph. The target problem has been modeled for a holding company which is a supply chain for Covid-19 drugs. Then the problem was solved using Multi-Objective Particle Swarm Optimization (MOPSO) metaheuristics algorithm and NSGAII multi-objective genetic algorithm. A comparison was carried out between these two methods and the results indicated that MOPSO performed better.

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“…e integrated performance of suppliers, manufacturers, distributors, and customers, which make up the components of the supply chain, has been studied signi cantly during recent years [1][2][3]. From an operational perspective, supply chain management is to integrate the suppliers, manufacturers, warehouses, and storage centers in an e ective manner, so that goods are produced and distributed in the right quantities, at the right time, and in the right place in a way that minimizes the cost of the entire system while maintaining a proper level of customer service [4,5].…”

Section: Introductionmentioning

confidence: 99%

Presenting a Multi‐Echelon and Multi‐Product Model for Inventory Control considering Shortages Using a Heuristic Algorithm

Ara

Toofani

Kaveh

et al. 2022

Discrete Dynamics in Nature and Society

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In the present study, a mathematical model is provided for inventory management in a three-level supply chain including a supplier, a manufacturer, and a distributor, taking into account the potential for product deficiency. Significant parameters such as the optimal order size for raw materials, optimal production rate, optimal allowed deficiencies at each supply chain level, the of the vehicles and the number of times the products are delivered between the supply chain components have been provided aiming at minimizing inventory management costs in the supply chain. The problem was solved using a heuristic algorithm. The proposed model is implemented for 20 different numerical examples. According to the results, the difference between the solutions obtained from the algorithm and the solutions obtained from the optimal values with the real variables is an average of 1.52%.

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A closed-loop supply chain configuration considering environmental impacts: a self-adaptive NSGA-II algorithm

Cited by 52 publications

References 45 publications

Impacts of green and preservation technology investments on a sustainable EPQ model during COVID-19 pandemic

Impacts of green and preservation technology investments on a sustainable EPQ model during COVID-19 pandemic

Presenting an Agile Supply Chain Mathematical Model for Covid 19 (Corona) Drugs Using Metaheuristic Algorithms (Case Study: Pharmaceutical Industry)

Presenting a Multi‐Echelon and Multi‐Product Model for Inventory Control considering Shortages Using a Heuristic Algorithm

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