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This paper proposes an integrated inventory model of a supply chain system consisting of a single manufacturer and single buyer under stochastic demand. The model considers carbon tax regulation to reduce supply chain operations' emissions. To comply with this regulation, the manufacturer invests in green production technologies and replaces the existing (conventional) facility with a green facility. Thus, the manufacturer can benefit by implementing a hybrid production system involving the simultaneous operation of a conventional and a green facility. The green facility requires higher production costs than the conventional facility, but its emissions are lower. The demand is stochastic and the average demand rate is influenced by the product selling price and green investment level. The goal of this research is to determine the optimal delivery lot, number of shipments, safety factor, selling price and investment level in order to optimize the joint total profit. An efficient algorithm is proposed to solve the problem and a numerical example is provided to demonstrate the applicability of the proposed model. A sensitivity analysis is performed to evaluate the impact of the model's key parameters on its behavior. The results show that green investments made by the manufacturer can effectively reduce the total emissions generated from the supply chain and increase the product's selling price. Furthermore, a hybrid system operated by the manufacturer is proven to control costs and emissions, especially in situations in which the replacement of production facilities must be performed gradually based on the available investment budget. [Display omitted] • A manufacturer-retailer inventory model is proposed under stochastic demand. • Manufacturer uses a hybrid production composed of two facilities. • Demand rate is influenced by the selling price and green investment factor. • Carbon emissions are produced from transportation, storage and production activities. • A carbon tax policy is adopted to minimize emissions. [ABSTRACT FROM AUTHOR]

Controlling carbon emissions and improving biofuel generation are crucial for every manufacturer. The responsible managers' primary concern is to increase profit and form a sustainable supply chain. Further, supply chain managers select appropriate combinations when dealing with minimizing waste, quality improvement of biofuel, and multi-mode transportation. The study's objective is to show the combined effects of improved quality of biofuel and controlling carbon emissions in a smart three-echelon sustainable supply chain management. In this model, one-manufacturer, one-supplier, and multi-retailers are contemplated. When the supplier makes impure biofuel, it transports to the manufacturer for pure biofuel. A random production rate is applied through a smart production system; still, impure biofuel is produced. For that reason, a two-stage inspection policy with a variable manufacturing rate is considered to make the production process flexible such that the quantity of impure biofuel is reduced and impure biofuel treated as a waste. After production, the manufacturer transports pure biofuel to multi-retailers. A variable selling price-dependent demand is introduced for the maximization of profit. The carbon emissions are considered, which are associated with different operational activities of inventory such as preparation of setup of suppliers, manufacturers, transportation of products, and holding stock at manufacturers and the retailer's end. The retailers keep up the actual order as on demand to the manufacturer to save from the excess holding costs. The model has been solved with a specific algebraic procedure to obtain the global optimum solution. Four numerical experiments are conducted to ensure the model's effectiveness and profit maximization. The results indicate that these three echelons' smart production significantly minimized impure biofuel and carbon emissions, positively impacting the environment and the finance, attached to the inventory. The proposed integrated system's validity is illustrated with sensitivity analysis, numerical examples, and graphical representation. In addition, various worthy managerial insights based on the study are provided. [Display omitted] • Energy consumption and carbon emissions are minimized by using flexible production. • The characteristic of biofuel is enhanced by two stage inspection policy. • A robust multi-mode of transportation policy is addressed. • Profits are maximized with variable demand, which is selling price dependent. [ABSTRACT FROM AUTHOR]

This paper analyses the decision behaviour and coordination mechanisms for a two-echelon sustainable supply chain under a cap-and-trade regulation. In a make-to-order setting, carbon emissions are generated primarily by the downstream manufacturing process, and the market demand of the supply chain is affected by two decision variables, the sustainability level and the selling price. The impact of the unit emissions trading price on the optimal decision variables in both centralized and decentralized systems is revealed. The comparison of decentralized and centralized systems shows that the increase in total profit in centralized system is at most 1/3 that in decentralized system. To achieve the same profit as the centralized system, we consider two contracts to coordinate the sustainable supply chain, revenue-sharing and two-part tariff contracts. By analysing the conditions for a win-win outcome, we prove that only the two-part tariff contract can lead to perfect coordination. Finally, sensitivity analysis of the key parameters is undertaken as part of a numerical example illustrating the theoretical results. [ABSTRACT FROM AUTHOR]

Biofuel manufacturing from renewable biomass through a smart manufacturing system is an important alternative to fossil fuels, which helps to decrease dependability on conventional fuel and decrease carbon emanations. By utilizing efficient labors, smart machines, and minimized energy utilization, the conventional biofuel manufacturing framework can be converted into a smart sustainable manufacturing framework. The existing conventional fuel demand can be replaced by biofuel. This study efforts to make pure biofuel with less amount of carbon emanations and energy utilization through a smart multi-type biofuel manufacturing framework, where the demand of the biofuel is selling price dependent. The different energy costs including air handling cost, lighting cost are calculated in this work-in-process inventory. The carbon emissions cost is included in every stage of this model. A variable demand has introduced for the maximization of profit. To reduce energy consumption and carbon emissions, a two-stage inspection cost with a variable manufacturing rate is taken to make the manufacturing process flexible such that the amount of impure biofuel is minimized. Although a random manufacturing rate is applied through a smart manufacturing system, still impure biofuel is manufactured. The impure biofuel is remanufactured again through refining just after the well-planned manufacturing ends. In this model, the multi-delivery technique is used such that a fixed amount of biofuel of n segments of the pure biofuel is transported to market places at predetermined intervals at the time of delivery frame. The classical optimization technique is used for continuous and differentiable variables and the mixed integer programming technique is utilized for discrete variables to maximize the total profit globally. To validate the model's usefulness, four numerical observations are studied. It is shown that by utilizing the said procedure, the percentage of impure biofuel can be decreased truly through the minimized energy consumption. The graphical representation and the sensitivity experiment show the impact of every parameter with the whole cost of the research paper. Numerical results assist to get the maximum profit and the optimum selling price of biofuel globally in a sustainable smart multi-type biofuel manufacturing system. [Display omitted] [ABSTRACT FROM AUTHOR]

In today's environment, it is difficult to be successful without considering sustainability. The effects of global warming are becoming more observable in daily life. Supply chain activities are important sources of environmental emissions. This effect increases concerns to control emissions through the development of a supply chain inventory model. A replenishment problem based on joint pricing, dynamic investment in environmental cost, order cost, preservation technology cost, and optimal replenishment times for a non-instantaneous deteriorating item is considered as a way to maximize retailer profit. In this problem, the demand rate depends on the stock and selling price. An Algorithm is used to find the optimum solution of the supply chain inventory problem, which determines the selling price, preservation technology investment cost, environmental emission cost, order cost, and replenishment cycle time. Theoretical analysis of the optimal properties of the proposed model is provided, and then solution methods are proposed. Numerical analysis is conducted to show the application of the model. Managerial implications are given to practitioner. This study demonstrates that the proposed model could be applied under real-world situations. • A decision-making problem is studied to find an optimal investment of environmental emissions cost. • The demand rate depends on price, and inventory level. • Managerial insights into the structure of inventory policies are given. • Investment in preservation technology is profitable. [ABSTRACT FROM AUTHOR]