Green Closed-loop Supply Chain Research Articles

Multi-Objective Green Closed-Loop Supply Chain Management with Bundling Strategy, Perishable Products, and Quality Deterioration

This study presents a four-objective mathematical model to improve closed-loop supply chain (CLSC) management. The aim of this research is to reduce the costs of the entire chain, risk, emission of pollutants, and time to deliver the product to the customer in uncertain demand condition. In this paper, the NSGAII algorithm is used to solve the model. In this algorithm, among the answers of each generation, a number of them are selected using the two-run tournament selection method. In the binary selection method, the answers are randomly selected from the population, and then a comparison is made between these two answers, and whichever is better is finally selected. The selection criteria in NSGA-II are, firstly, the rank, and secondly, the crowding distance related to the answer. Also, the performance of the NSGA-II algorithm on the same model and data has been compared with the MOPSO algorithm. In the proposed algorithm, if it encounters an impossible solution, it exits the local mode and solves the problem in global conditions. The results show that the proposed method strikes a better balance between discovery and efficiency criteria and avoids falling into local optima. Therefore, in addition to its effectiveness in discovering optimal answers, the genetic-based method has high speed and subsequently, high convergence and diversity rates compared to the particle swarm method. Also, compared to previous methods in the green closed-loop supply chain, the proposed method is better than the modified genetic algorithm, reducing the costs of the chain by about 2.38%.

A closed-loop green supply chain with retailers' competition and product recycling in the green environment under the cap-and-trade policy

<abstract><p>Nowadays, product recycling has become an effective strategy for manufacturing industries to achieve sustainable development due to the scarcity of natural resources, waste management, and greenhouse gas emissions. This study considered an imperfect production-based competitive supply chain model for product recycling in an emission-reduction environment under a cap-and-trade scheme. The manufacturer invests in green technology to restrict carbon emissions during production. The recycler collects used items at a recovery rate depending on the buy-back price and environmental awareness effort. The rival retailers compete against each other for the retail price and promotional effort. The linear type of market demand depends on the retail price, promotional effort, and green level of the product. The proposed model was analyzed analytically and numerically under one centralized system, five decentralized systems, three Stackelberg, and two Nash game structures. Numerical examples and sensitivity analysis of the key parameters were studied to justify the feasibility of the proposed model. The present study revealed that the centralized scenario is mostly preferable for supply chain profit. The manufacturer-Stackelberg 1 scenario is most profitable for the manufacturer, whereas the two retailers collect maximum individual profit in the vertical Nash 2 model, where they jointly play the game. Moreover, retail price plays a crucial role in optimizing individual retailers' profits in the competitive market. In connection with the environmental aspects, the government should offer lower carbon caps to curtail excessive emissions and restrict the selling of excess carbon quotas.</p></abstract>

Dual-objective optimization of a green closed-loop supply chain in steel industry considering quantity discount

Dual-objective optimization of a green closed-loop supply chain in steel industry considering quantity discount

Recycling Strategy of Green Closed-Loop Supply Chain Under Urban and Rural Low-Carbon Planning

Abstract The low-carbon ecological city aims to harmonise sustainable urban development with low-emission planning approaches. Emissions from business production processes are central to low-carbon planning. This paper explores three closed-loop supply chain recycling models - manufacturer, retailer, and third-party -considering carbon trading and emission reduction technology investment. Respective Stackelberg game models are developed incorporating carbon emission reduction costs, recycling costs, carbon trading price, emission intensity, and recycling price. The influence of these variables on carbon emission reduction and profit is examined through numerical analysis. Results indicate the government’s free carbon quota does not impact per-unit carbon reduction or manufacturer profit, nor optimal recycling mode selection. Under specific remanufacturing emission intensity and production cost saving conditions, carbon quota trading can substantially incentivise manufacturers to invest in emission reduction and recycling. With carbon trading and emission reduction technology investment, manufacturer recycling optimises economic and environmental benefits when remanufactured products provide high production cost savings. This fosters sustainable development supporting low-carbon planning.

Prevention of post-pandemic crises: A green sustainable and reliable healthcare supply chain network design for emergency medical products

The COVID-19 pandemic happened exactly when no one expected it and many people died due to the lack of medical equipment. Although pulse oximeters and thermometers were only one of the virus detection equipment, the lack of that equipment could lead to people not knowing about the disease and then the death of those people. Given that these medical devices are very vital in the era of a pandemic, and much less in the later, it is required to provide the best conditions for their use in a closed-loop healthcare supply chain network in post-pandemic. In this paper, a scenario-based two-stage stochastic programming three-objective model for designing a green closed-loop supply chain network is presented. Cost minimization, reliability maximization, and critical response maximization are the objectives of the proposed model. The third objective function is considered for the critical response based on the choice of transportation method. The greenhouse gas emissions for all supply chain elements are considered uncertain and controlled in several possible scenarios. By using an accelerated Benders decomposition algorithm, the mathematical model was solved in different dimensions and the result was analyzed and evaluated in different scenarios. The results demonstrate that the acceleration of Benders bonds reduces the convergence speed of the algorithm by 41%. Our study provides managerial insights into sustainability and reliability, enhancing healthcare supply chain resilience during and after pandemics.

Pricing and bundling strategies for complementary products in a closed-loop green supply chain under manufacturers’ different behaviors

This study attempts to incorporate product complementarity and bundling strategy with green innovation and remanufacturing in a two-stage supply chain. For doing so, it considers a green closed-loop supply chain that combines two manufacturers and a typical retailer to deal with complementary products. Based on the manufacturer-led Stackelberg game-theoretic approach, it first develops two models considering the bundling strategies of the retailer. Each of these two models again establishes three sub-models under consideration of whether the manufacturers make their decisions jointly or simultaneously or sequentially. The optimal responses and the profitability under various models are compared both analytically and numerically to get some insights. The results exhibit that (a) regardless of different bundling strategies, the sequential decision-making scenario is beneficial for the leading manufacturer while the joint decision-making scenario is profitable for another manufacturer, the retailer, and the entire supply chain, (b) no bundling strategy is preferable in a green-sensitive market, even though it gives less profit to channel individuals, (c) in the Stackelberg scenario, the decision of which of two manufacturers will profit more depends on product complementarity and the residual values obtained from end-of-used products acquisition and their handling, and (d) the level of product complementarity and bundle price discount play important role in determining the appropriate bundling strategy.

Pricing strategies in a dual-channel green closed-loop supply chain considering incentivized recycling and circular economy

In recent years, significant attention has been dedicated to the design of closed-loop supply chains. However, opportunities exist to refine modeling approaches in alignment with circular economy principles. This refinement could foster the collaborative involvement of customers and retailers, resulting in a more sustainable operational framework. This study aims to address this gap, fostering waste reduction, resource conservation, and collaborative engagement in closed-loop supply chains. Thus, a multi-level, dual-channel green closed-loop supply chain that integrates circular economy principles is examined. We focus on implementing an incentive-based recycling program and examining various closed-loop supply chain settings: centralized, decentralized, and collaborative. We aim to determine optimal equilibrium prices, greening levels, and advertising strategies while considering the concurrent aspects of greening and incentivized recycling in today environmentally conscious era. By developing a demand function that integrates price elasticity, cross-price impacts, sustainability, and advertising, we evaluate performance through numerical examples and a case study in the clothing industry. The findings indicate that a collaborative approach surpasses a decentralized one regarding sustainability, guaranteeing profitability across the supply chain. The study also underscores the trade-offs between centralization and decentralization, with the former failing to ensure maximum individual profitability despite augmenting overall chain profits. Our findings can guide managers in reconciling profitability with sustainability when choosing supply chain structures, accentuating the value of collaborative strategies and green cost-sharing contracts. Furthermore, our results highlight that targeted advertising can stimulate demand for green products, and incentivizing circular economy practices through collaboration can yield positive environmental and economic outcomes.

Analysis of Green Closed-Loop Supply Chain Efficiency under Generalized Stochastic Petri Nets

In this paper, we aim to explore the operational performance of a green closed-loop supply chain under random events. A green closed-loop supply chain model based on generalized stochastic Petri nets (GSPN) is built using the Petri nets theory. According to the isomorphic relationship between GSPN and continuous-time Markov chains, the relevant Markov model is converted from GSPN, and the steady-state probability of the model is then calculated. Finally, the model is analyzed from the aspects of time performance and operation efficiency of each link. Compared to previous studies, this paper finds that: when the whole green closed-loop supply chain system reaches a dynamic equilibrium state, the product has a steady-state probability at all stages, and thus the overall operational performance of the system can be obtained; compared with the recycling of waste products, the green product takes a longer time in the production and distribution stages; since marketing, packaging processing, market feedback, and market demand formulation account for a high level of utilization throughout the life cycle of green products, decision makers need to focus on the supervision and management of these links. Managers of green closed-loop supply chain systems need to adjust their decision-making strategies in a timely manner according to the performance level of the system in the steady state to realize the efficient operation of the system. This paper not only provides theoretical support for the improvement of the operational efficiency of green closed-loop supply chain system, but also provides new ideas for the research of green closed-loop supply chain operation mode.

A Fuzzy Programming Based Approach to a Multi-Objective Multi-Echelon Green Closed-Loop Supply Chain Problem

Abstract It has become a social and legal obligation to take into account environmental factors as well as economic factors when designing the supply chain network. Reducing the emission of harmful gases in supply chain operations, recycling and efficient use of resources must be taken into consideration for future generations. The supply chain created in this study, in addition to the abovementioned features, includes supplier selection, warehouse and distribution center setup, transportation amounts between facilities, and transportation modes of products to be transported. This model, which is a multi-objective multi-echelon green closed-loop supply chain, is a mixed integer linear mathematical model and tries to maximize the joint satisfaction of the objectives with the help of a fuzzy approach using Zimmermann’s minimum operator.

Evolutionary game analysis for non-cooperative behavior of entities in a closed-loop green supply chain under government intervention

Evolutionary game analysis for non-cooperative behavior of entities in a closed-loop green supply chain under government intervention

Toward circular economy for pomegranate fruit supply chain under dynamic uncertainty: A case study

Food security is a fundamental prerequisite of human survival. This study focuses on providing a novel bi-objective model for the design of a green closed-loop pomegranate supply chain based on the value chain. To maximize the benefits of circular economy, we propose a thermochemical conversion process and develop a novel hybrid risk-neutral and risk-averse multi-stage stochastic programming (RNRAMSSP) approach to cope with supply uncertainty. We employ the expected value of perfect information (EVPI) and value of stochastic solution (VSS) to validate the proposed approach. For the VSS metric, we define a novel measure to compare the worst-case cost of the stochastic and deterministic model solutions. To demonstrate the applicability of the proposed model, we provide a real case study in Iran. Based on the VSS metric, the risk-neutral and risk-averse stochastic model solutions save up to 1% and 1.76% in the worst-case cost, respectively, compared to the deterministic model.

Designing a closed-loop green outsourced maintenance supply chain network for advanced manufacturing systems with redundancy strategy and eco-friendly parts

Designing a closed-loop green outsourced maintenance supply chain network for advanced manufacturing systems with redundancy strategy and eco-friendly parts

Research on Power Battery Recycling in the Green Closed-Loop Supply Chain: An Evolutionary Game-Theoretic Analysis

The used power batteries of new energy vehicles have become a combined issue of environmental pollution, resource scarcity, and economic sustainability. Power battery recycling is inevitably becoming the key link in the formation of the green closed-loop supply chain for new energy vehicles and the green cycle of the new energy vehicles industry. This study establishes a three-party evolutionary game model of “new energy vehicle manufacturers, power battery manufacturers, and power battery recyclers”, simulates the dynamic evolution process of each game player’s strategy, and analyzes the effects of the digital transformation factor and other factors leading to the evolution trend. The main results show that: (i) in the absence of sufficient incentives and constraints, the green closed-loop power battery supply chain cannot be formed naturally; (ii) digital transformation is an important factor in the journey of the green closed-loop supply chain for power battery recycling, and (iii) government rewards and penalties can promote the formation of the green closed-loop supply chain for power batteries. This research innovatively investigates the concept of the green closed-loop power battery supply chain and its formation mechanism, which provides theoretical support to promote the recycling of used power batteries to achieve sustainability.

Pricing and greening decisions of a government-subsidised dual-channel closed-loop green supply chain model with price-dependent collection rate

ABSTRACT Online shopping has become increasingly popular among customers due to the availability and easy accessibility of electronic devices. Hence, a manufacturer would like to open an online platform with his traditional retail channel. Government subsidies are endogenised in a research joint venture based on recent observations. Here, government subsidies are assumed to increase the production of eco-friendly products to be much more environmental friendly. The retailer and third-party collector collect used products from the customer and return them to the manufacturer for recycling. Demand rates are modelled as linear functions of selling prices and the level of green innovation. The collection rates are considered linear functions of collecting fees and the level of green innovation. The study investigates three decentralised models under three scenarios and the centralised model. A sensitivity analysis is composed to study the effects of the essential parameters. Critical managerial insights have been provided, which is beneficial for the supply chain members. If the cost co-efficient of green innovation can be reduced, then the optimal level of green innovation and the members' profits increase. Again the governmental subsidy is directly proportional to the level of green innovation and the manufacturer's profit.

Green Closed-Loop Supply Chain Networks’ Response to Various Carbon Policies during COVID-19

As concerns about the environment continue to increase and restrictions become tougher, professionals in business and legislators are being compelled to investigate the environmental effects of the activities associated with their supply chains. The control of carbon emissions by governments all over the world has involved the adoption of a variety of strategies to lower such emissions. This research optimizes COVID-19 pandemic logistics management as well as a green closed-loop supply chain design (GCLSCD) by basing it on carbon regulatory rules. This research looks at three of the most common types of normal CO2 restrictions. In the models that have been proposed, both costs and emissions are optimized. When it comes to supply chain (SC) activities, there is a delicate balance to strike between location selection, the many shipment alternatives, and the fees and releases. The models illustrate these tensions between competing priorities. Based on the numerical experiment, we illustrate the impact that a variety of policies have on costs in addition to the efficiency with which they reduce emissions. By analyzing the results of the models, managers can make predictions concerning how regulatory changes may affect overall emissions from SC operations.

Research on Green Closed-Loop Supply Chain Considering Manufacturer’s Fairness Concerns and Sales Effort

To reduce resource loss and environmental pollution, green CLSC has become a hot issue that manufacturing enterprises pay attention to. In green CLSC, manufacturers would pay attention to the fairness of profit distribution when making sales efforts. Therefore, this paper studies a green closed-loop supply chain (CLSC) considering manufacturer sales efforts and fairness concerns. Then, the centralized model and decentralized model are built and analyzed. Afterward, a profit-sharing contract between members is designed to coordinate the supply chain. We made the following observations: (1) The manufacturers’ fairness concerns would reduce product green degree, sales effort and recycling rate of used products, which is not conducive to the sustainable development of the green closed-loop supply chain. (2) When the manufacturers’ fairness concerns are gradually strengthened, the optimal decisions would deviate even more from the optimal equilibrium results. (3) When the coefficient of fairness concerns and the ratio of profit-sharing satisfy a certain range, Pareto improvement can be effectively realized.

Multi-objective closed-loop green supply chain model with disruption risk

The benefits of the circular economy are pushing industries towards forming closed-loop supply chains (CLSCs). This transition requires the industries to deal with conventional cost minimization along with various environmental objectives. However, the objectives become difficult to attain if the production process gets disrupted and no suitable recovery mechanism is in place. The extant literature indicates that few researchers have worked to develop a recovery model for CLSC systems that considers both economic and environmental objectives. Thus, this study develops a nonlinear complex mathematical model to minimize the total cost, energy consumption, CO2 emission, and waste generation of supply chains with a focus on disruption risk. This research contributes to the literature by addressing the model with three existing heuristics — multi-objective genetic algorithm (MOGA), non-dominated sorting genetic algorithm (NSGA-II), and multi-objective bonobo optimizer (MOBO)–and by developing an updated hyper-heuristic algorithm based on a choice function. We employ four performance metrics–algorithm effort (AE), ratio of non-dominated individual (RNI), maximum spread (MS), and average distance (AD)–to compare the efficiency and effectiveness of these algorithms. Our quantitative results show that RSCs can mitigate production shortages stemming from supply chain disruptions. They also demonstrate the benefits of CLSCs with regard to lowering costs, energy consumption, CO2 emissions, and waste generation.

Risk-averse joint facility location-inventory optimisation for green closed-loop supply chain network design under demand uncertainty

Risk-averse joint facility location-inventory optimisation for green closed-loop supply chain network design under demand uncertainty

Risk-Averse Joint Facility Location-Inventory Optimization for Green Closed-Loop Supply Chain Network Design under Demand Uncertainty

Risk-Averse Joint Facility Location-Inventory Optimization for Green Closed-Loop Supply Chain Network Design under Demand Uncertainty

Green Closed-Loop Supply Chain Network Design During the Coronavirus (COVID-19) Pandemic: a Case Study in the Iranian Automotive Industry.

This paper presents a new mathematical model of the green closed-loop supply chain network (GCLSCN) during the COVID-19 pandemic. The suggested model can explain the trade-offs between environmental (minimizing CO2 emissions) and economic (minimizing total costs) aspects during the COVID-19 outbreak. Considering the guidelines for hygiene during the outbreak helps us design a new sustainable hygiene supply chain (SC). This model is sensitive to the cost structure. The cost includes two parts: the normal cost without considering the coronavirus pandemic and the cost with considering coronavirus. The economic novelty aspect of this paper is the hygiene costs. It includes disinfection and sanitizer costs, personal protective equipment (PPE) costs, COVID-19 tests, education, medicines, vaccines, and vaccination costs. This paper presents a multi-objective mixed-integer programming (MOMIP) problem for designing a GCLSCN during the pandemic. The optimization procedure uses the scalarization approach, namely the weighted sum method (WSM). The computational optimization process is conducted through Lingo software. Due to the recency of the COVID-19 pandemic, there are still many research gaps. Our contributions to this research are as follows: (i) designed a model of the green supply chain (GSC) and showed the better trade-offs between economic and environmental aspects during the COVID-19 pandemic and lockdowns, (ii) designed the hygiene supply chain, (iii) proposed the new indicators of economic aspects during the COVID-19 outbreak, and (iv) have found the positive (reducing CO2 emissions) and negative (increase in costs) impacts of COVID-19 and lockdowns. Therefore, this study designed a new hygiene model to fill this gap for the COVID-19 condition disaster. The findings of the proposed network illustrate the SC has become greener during the COVID-19 pandemic. The total cost of the network was increased during the COVID-19 pandemic, but the lockdowns had direct positive effects on emissions and air quality.