Green Closed-loop Supply Chain Research Articles

Design and Site Selection of Reverse Logistics Network for Iron and Steel Enterprises from the Perspective of Green Supply Chain

The iron and steel industry is not only one of the most important components of China's national economy, but also a typical resource-and-energy-intensive industry. Under the background of "Carbon Peaking and Carbon Neutrality Goals", it is of great significance for the iron and steel industry to improve the green closed-loop supply chain and develop circular economy. From the perspective of green supply chain, this paper puts forward the three-level network structure of waste steel reverse logistics based on the present situation of waste steel recycling in China, and uses k-means clustering algorithm and accurate center of gravity method to select locations for the primary and secondary nodes. The purpose of this paper is to provide a basis for iron and steel enterprises to carry out network optimization of reverse logistics.

Configuration and optimisation of a green closed-loop supply chain with delivery time and green investment considering government subsidy under meta-heuristics algorithms

Consumers' environment consciousness, together with the fierce rivalries among companies, has attracted increasing attention from scholars and industries to the configuration and optimisation of green closed-loop supply chain. However, current studies of closed-loop supply chains rarely consider both the uncertainty from the market and the quality from the recycled used products. Therefore, this article constructs a green closed-loop supply chain total profit model that considers government subsidies, delivery times, green investment and the above uncertainties. Fuzzy chance constraint method is used to solve the uncertain demand; genetic and particle swarm optimisation algorithms are adopted to calculate the model. This study finds (1) enterprises can formulate flexible and adaptable strategies based on different demands; (2) their delivery time decisions rely on both consumer demand and their logistics development levels; (3) enterprises should adjust their delivery times and green investment decisions according to consumers' different sensitivities; (4) enterprises can increase profits by recycling products within a certain range of greenness; (5) for improving recycling and remanufacturing rates, the government can provide secondary subsidies to enterprises for product recycling within the green range of 0.35 ∼ 0.40. This study contributes to the optimisation of strategies developed by enterprises under conditions of subsidies and multiple uncertainties.

A new approach for reliability modeling in green closed-loop supply chain design under post-pandemic conditions: A case study

Climate change, pandemics, and economic crises have created complex challenges for supply chains. Managing such situations requires the development of reliable decision-making frameworks. In this paper, a multi-level, multi-product, and multi-period closed-loop supply chain is studied with environmental considerations. A bi-objective mixed-integer linear programming model is presented for facility location, flow allocation, and transportation mode determination. The objectives of the model are to minimize the total cost and maximize the reliability of suppliers to meet the needs of factories. In the area of reliability engineering, a new approach is defined for modeling the probability of supplier availability considering catastrophic failures caused by pandemics, economic sanctions, and other failure modes. Furthermore, the decision-maker can handle the emission of greenhouse gases by an upper-bound constraint. In order to face the simultaneous uncertainty of demand and the maximum CO2 emission allowed, a scenario-based two-stage stochastic programming approach is proposed. The improved version of the augmented ε-constraint method, known as AUGMECON2, is used to solve the proposed model. The efficiency of the model and the proposed solution approach are investigated through a real-world case study of a battery manufacturing company in Iran.

An integrated planning approach for perishable goods with stochastic lifespan: Production, inventory, and routing

This paper focuses on addressing the crucial challenges posed by the uncertainty surrounding perishable goods within the supply chain. With staggering socioeconomic costs and significant environmental implications, effective management of perishable goods emerges as a critical imperative. Globally, the annual loss of approximately 14% of food, amounting to a staggering USD 1 trillion, highlights the urgency of the issue. However, Prevailing classification methods for perishable products oversimplify their complexity by dividing them into fixed or variable lifespans, neglecting the random lifespans endured due to fluctuating storage conditions, blurring traditional boundaries between fixed and variable classifications. In response to these pressing challenges, the research proposes a novel approach: the development of a nonlinear mixed-integer programming model for a green closed-loop supply chain. This innovative model seamlessly integrates production, inventory, and routing decisions for both main and secondary products of a manufacturer. Moreover, it optimizes order splitting and transportation modes to efficiently convert perished items into raw materials under conditions of uncertainty. Central to the approach is the adoption of a scenario-based methodology to model uncertainties, particularly focusing on the variability in the lifespan of perishable products. This approach allows for a more nuanced understanding of the complex dynamics inherent in managing perishable goods within the supply chain. To solve the proposed model, a novel hybrid algorithm is introduced: the Particle Swarm Optimization (PSO) and Simulated Annealing (SA) algorithm, or PSOSA, ensuring robust optimization under uncertainty and enhancing decision-making within the perishable goods supply chain. The research findings underscore the inadequacy of prevailing assumptions regarding the fixed lifespan of perishable products, commonly observed in the literature. By accounting for uncertainty in perishable goods’ lifespan, a more accurate representation of total producer costs is achieved, highlighting the misleading reduction of 25% observed when neglecting such uncertainty.

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>

A Bi-objective Model for Locating and Allocating in a Green Closed-loop Supply Chain by Probabilistic Customers

A Bi-objective Model for Locating and Allocating in a Green Closed-loop Supply Chain by Probabilistic Customers

Designing a Green Closed-Loop Supply Chain Network with Considering Different Levels of Production Technologies and Transportation Modes

Designing a Green Closed-Loop Supply Chain Network with Considering Different Levels of Production Technologies and Transportation Modes

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.