Environmental constraints in joint product and supply chain design optimization

Carbon emissions reduction in supply chain is an effective method to reduce the greenhouse effect. The paper investigates the impacts of carbon trading price and consumers’ environmental awareness on carbon emissions in supply chain under the cap-and-trade system. Firstly, it analyzes the centralized decision structure and obtains the requirements to coordinate carbon emissions reduction and order quantity in supply chain. Secondly, it proposes the supply chain coordination mechanism with revenue-sharing contract based on quantity discount policy, and the requirements that the contract parameters need to satisfy are also given. Thirdly, assuming the market demand is affected by consumer’s environmental awareness in addition form, the paper proposes the methods to determine the optimal order quantity and the optimal level of carbon emissions through model optimization. Finally, it investigates the impacts of carbon trading price on carbon emissions in supply chain. The results show that clean manufacturer’s optimal per-unit carbon emissions increase as the carbon trading price increases, while nongreen manufacturer’s optimal per-unit carbon emissions decrease as the carbon trading price increases. For the middle emissions manufacturer, the optimal per-unit carbon emissions depend on the relationship between the carbon trading price and the carbon reduction coefficient.

Hydrogen is increasingly recognized as a key player in future energy systems. However, its production technologies�Steam Methane Reforming (SMR) and electrolysis�present trade-offs. SMR, the dominant method, is cost-effective but has a significant carbon footprint, emitting substantial greenhouse gases (GHGs). In contrast, electrolysis, powered by renewable energy sources, offers a cleaner alternative, albeit at a higher cost. While current hydrogen system optimizations primarily focus on cost reduction and GHG mitigation, they often neglect broader environmental impacts. This paper addresses the challenge of modeling a hydrogen supply chain (HSC) that achieves strong environmental performance at a relatively affordable cost. To this end, a supply chain design optimization is coupled with Life Cycle Assessment (LCA). The novelty of this work lies in the integration of multiple LCA indicators in the supply chain design optimization, rather than focusing solely on costs and Global Warming Potential. The model employs a multi-period (2025�2050) mixed-integer linear programming (MILP) formulation, implemented in the General Algebraic Modeling System (GAMS) environment, using CPLEX as the solver. The Bourgogne-Franche-Comt� region is used as a case study to illustrate the framework. Initial optimization results highlight how varying the focus on different parameters can lead to distinct solutions and provide insights into the interactions between indicators. Future research will aim to reduce the dimensionality in multi-objective optimization to improve efficiency while maintaining environmental sustainability in the development of hydrogen networks.

Carbon emission constraints and trading policies in e-commerce environments have brought huge challenges to the operation of supply chain enterprises. In order to ensure the good operation of the e-commerce supply chain in a low-carbon environment, a supply chain scheduling optimization method based on integration of production and transportation with carbon emission constraints is proposed; we use it to analyze the impact of centralized decision-making mode and decentralized decision-making mode on supply chain scheduling and establish a scheduling optimization model that aims at optimal carbon emissions and costs. A multilevel genetic algorithm was designed according to the characteristics of the model, and numerical examples are used to verify the effectiveness of the model and algorithm. The results show that the centralized decision-making mode plays the role of the carbon emission constraints to the greatest extent; the carbon emissions and the cost are smallest in the centralized decision-making mode. The decentralized decision-making mode leads to the overall cost preference of the supply chain due to separate decisions made by enterprises, and the carbon emissions in the supply chain are greater. Transportation experts, business managers and government departments are interesting for integrated production and transportation scheduling in e-commerce supply chain with carbon emission constraints. Further research should address integrated production and transportation scheduling in dual-channel low supply chains.

Cities are the main spaces to study a low-carbon economy. This paper introduces basic concepts covering “tolerance of planning carbon emissions,” “inevitable carbon emissions” and “excessive carbon emissions,” then discusses the problem with optimal city carbon emissions under the condition of tolerance. Theoretical analysis and scenario analysis were employed. First, according to optimal allocation theory of resources, we discuss how optimal society carbon emissions take place. Then, the deviation of optimal city carbon emissions was explored and analyzed, which was mostly caused by the missing price of carbon emissions allowance, excessive carbon emissions, and so on. Third, we analyzed optimal city carbon emissions under different conditions, in which different types of tolerance were included. Results show that theoretical investigations on optimal city carbon emissions provide relative ideas for determining control index and optimizing control countermeasures. Policy implications include improving the control index of city carbon emissions through environment enhancement, setting a reasonable control index of city carbon emissions under the consideration of the relationship between city economy and its environment, and establishing trading allowance and compensation mechanism of city carbon emissions, etc.

PurposeThe coal-fired power plants have been confronted with new operation challenge since the unified carbon trading market was launched in China. To make the optimal decision for the carbon emissions and power production has already been an important subject for the plants. Most of the previous studies only considered the market prices of electricity and coal to optimize the generation plan. However, with the opening of the carbon trading market, carbon emission has become a restrictive factor for power generation. By introducing the carbon-reduction target in the production decision, this study aims to achieve both the environmental and economic benefits for the coal-fired power plants to positively deal with the operational pressure.Design/methodology/approachA dynamic optimization approach with both long- and short-term decisions was proposed in this study to control the carbon emissions and power production. First, the operation rules of carbon, electricity and coal markets are analyzed, and a two-step decision-making algorithm for annual and weekly production is presented. Second, a production profit model based on engineering constraints is established, and a greedy heuristics algorithm is applied in the Gurobi solver to obtain the amounts of weekly carbon emission, power generation and coal purchasing. Finally, an example analysis is carried out with five generators of a coal-fired power plant for illustration.FindingsThe results show that the joint information of the multiple markets of carbon, electricity and coal determines the real profitability of power production, which can assist the plants to optimize their production and increase the profits. The case analyses demonstrate that the carbon emission is reduced by 2.89% according to the authors’ method, while the annual profit is improved by 1.55%.Practical implicationsAs an important power producer and high carbon emitter, coal-fired power plants should actively participate in the carbon market. Rather than trade blindly at the end of the agreement period, they should deeply associate the prices of carbon, electricity and coal together and realize optimal management of carbon emission and production decision efficiently.Originality/valueThis paper offers an effective method for the coal-fired power plant, which is struggling to survive, to manage its carbon emission and power production optimally.

This paper focuses on the impact of consumers’ preference to low carbon in the emission-concerned supply chain. In an emission-concerned supply chain, the consumers are assumed to prefer to low-carbon products. In an emission sensitive market, emission reduction not only brings the higher production costs but also stimulates the inverse demand function. Therefore, this may be an opportunity for players of the supply chain to coordinate their two objectives: environmental pressure (to reduce carbon emissions for environment protection) and profit-seeking, which intuitively seem to be contradictory. In order to address this research focus, a novel emission-sensitive demand function is adopted, and an emission -sensitive cost function is introduced explicitly to capture the deviation production cost caused by emission reduction. Then the decision-making of each member in the emission-concerned supply chain is investigated. We find that the decision-maker of the supply chain will choose different emission reduction strategies for different cases. An inspiring result shows that the channel profit as well as the emission reduction increase in the consumers’ preference to low-carbon consumption simultaneously in particular cases. Moreover, several emission-concerned contracts are designed to coordinate the channel. Another finding is that the manufacturer’s optimal carbon emissions per unit product keeps the same as the centralised channel, no matter whether the supply chain is coordinated or not. Furthermore, the further discussion reveals that less eco-friendly production than the traditional, if lack of external regulation as well as internal moral self-discipline, might be chosen under some specific conditions.

Methane emissions along biomethane and biogas supply chains are underestimated

This review paper provides the operations management (OM) community with an exhaustive analysis of the mathematical models developed for the problem of low-carbon supply chain management (LCSCM). Our paper belongs to the green supply chain management (GSCM) reviews but is distinguished by its specific interest in analysing research works on supply chain (SC) management regarding the reduction of carbon emissions and its related constraints. To facilitate our benchmarking of the 83 selected papers, we adopt a literature classification based on the logistic decisions studied within the developed models. We distinguish three categories of logistic decisions: operational management, technology investment and SC design coordination. Companies are currently facing great external pressures from governments and their conscientious customers to reduce their overall emissions. We analyse how these environmental constraints, which we believe are key drivers for low-carbon emissions management, have been incorporated into mathematical models. Analysing these external pressures in terms of concern about carbon emissions constitutes our main contribution through this literature review. In addition, companies are facing a challenge to reduce their carbon emissions, which are mainly generated from production, transport and storage activities. Consequently, the modelling of carbon emissions remains a crucial task when addressing the LCSCM problem. We suggest analysing the techniques used thus far to approximate those carbon emissions. Furthermore, to illustrate our literature classification and the features of the LCSCM problem, we provide the framework on which we based our analysis of the selected literature. We discuss the modelling aspects of this problem to highlight the limits of the existing literature and consequently suggest recommendations for future research. We believe that this issue will continue to be one of the top concerns of the OM community within the GSCM field as it continues to gain importance among business leaders, and political and social actors.

Low-carbon economy is the trend of economic development in the future. It is gradually becoming a hot topic in academic and business circles that how to reduce carbon emissions. Cap and trade is one of the effective ways to reduce carbon emissions and has been adopted by many countries. We investigate a two-echelon supply chain that consists of a supplier and a manufacturer. This paper assumes a vertical Nash game between the two sides. We study three different models on cap and trade policy, which are the independent carbon reduction model and the concentrated models (only the supplier faces cap and trade and only the manufacturer faces cap and trade). We obtain the optimal decisions and unit carbon emissions of the supplier and the manufacturer. The optimal wholesale price, sale price, unit carbon emission and maximum profit under different cap and trade models have be compared by numerical analysis. We find that concentrated carbon reduction models are beneficial for supply chain enterprises, but as the price is creating more carbon emissions than the independent model. This study provides valuable managerial implications, which will be beneficial for firms to make an important strategy.

Along with the increasingly environmental pollution, a carbon emission limiting scheme is proposed in many countries. Shenzhen becomes the first urban to operate the cap-and-trade carbon emission trading scheme in China. Besides, there’re six more cities entering the CTP trading in China. This paper focuses on the optimal pricing and carbon emission strategies of the manufacturer and retailer in a supply chain containing an upstream manufacturer who produces one particular kind product and a downstream retailer. We use two-stage Stackelberg game model to show how the supply chain functions. In view of the survey collected in Berlin, willingness to pay for clear production is different between residents there. Thus, consumers’ environmental awareness is introduced. In this model, the demand quantities are decided by the consumers, and both of the manufacturer and retailer can decide their own prices and carbon improvement degrees. The consumers’ environmental awareness can positively affect the demand of eco-friendly product. The carbon emission quantities can be transacted in the market. We find that as the consumers environmental awareness strengthens, the total revenue of manufacturer and retailer will increase. Besides, as the environmental awareness or the carbon transaction cost increases under certain conditions, the total carbon emission will decrease.

Design of responsive supply chains under demand uncertainty

Within the low-carbon supply chain network, variations in carbon emission reduction investment costs and product exhibition expenses among members at the same level can lead to distinct competitive behaviours. This study investigates the production decision of a supply chain operating within the framework of both green financing and a carbon cap-and-trade program. The manufacturer faces capital limitations and yield uncertainty. Green financing involves government subsidies on interest for low-carbon investment loans, while low-carbon subsidies are granted based on the manufacturer's carbon emission reductions. Our study investigates the effects of the green finance mechanism, carbon cap-and-trade scheme, and yield uncertainty on emission reduction decisions. This research illustrates the green finance subsidy with the low-carbon subsidy scheme. Additionally, we have analysed optimal production quantity and carbon emission levels in decentralised decision-making scenarios and extended our findings to joint supplier-manufacturer coalition contracts. Our findings demonstrate that both the green finance subsidy and the low-carbon subsidy contribute positively to reducing carbon emissions, while yield uncertainty exerts a negative influence. Additionally, risk-averse flexibility negatively impacts utility, while the joint coalition model guides decentralised decisions. Finally, managerial insights regarding supply chain profitability have been illustrated through green finance and the cap-and-trade system.

The manufacturing industry is a major source of greenhouse gas emissions (GHG). Additive manufacturing, owing to its multiple advantages, plays a critical role in innovating the current manufacturing industry, especially from a supply chain perspective. Currently, the majority of research on GHG emissions in the manufacturing industry is focused on traditional manufacturing, either single processes in the supply chain or specific case studies, indicating the lack of models on GHG emissions in additive manufacturing-enabled supply chain structures. In this work, a mathematical model is established to estimate the GHG emissions in both traditional manufacturing and additive manufacturing-enabled supply chains. To explore the advantages of additive manufacturing in terms of fast production and reduced or even eliminated the need for assembly and labor involvement, a unique integrated production-inventory-transportation structure is investigated in additive manufacturing case studies. The results indicate that a potential reduction of 26.43% of GHG emissions can be achieved by adopting the additive manufacturing technique in the supply chain. Also, the impacts of rush order rate, emission intensity, and vehicle GHG emission constant rate on the overall GHG emissions are investigated in the sensitivity analysis. Results indicate that a 20% variation in GHG emission intensity (the amount of CO2eq emissions caused by generating a unit of electricity) can lead to a 6.26% change in the total GHG emissions in additive manufacturing.

Cooperative inventory games in multi-echelon supply chains under carbon tax policy: Vertical or horizontal?

With the continuous increase of carbon emissions and the deterioration of environment, governments have passed various laws and regulations to force enterprises to take carbon emission abatement measures. As one of the regulations, carbon tax plays an important and positive role in environmental protection. For enterprises, the allocation of carbon emission abatement is a common means to promote emission reduction. In this paper, under the uncertain market demand, the option contract is adopted to study the retailer's optimal retail price and order quantity, as well as the manufacturer's optimal ratio of total carbon emission abatement and production quantity under the carbon tax. In addition, We analyze the optimal decisions and expected profits of supply chain members with respect to the carbon tax, total carbon emission abatement and option prices by analytical and numerical study, and find that (1) when the carbon tax increases, the optimal ratio of total carbon emission abatement and the optimal retail price increase, while the optimal order and production quantity decrease, which is contrary to the situation of the total carbon emission abatement; (2) when the option prices increase, the optimal retail price increases while the ratio of total carbon emission abatement and the optimal order and production quantity decrease; (3) the expected profits of the manufacturer and retailer show the same trend with the increase of carbon tax and total carbon emission abatement, while have the opposite trend with the increase of option prices.