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•Combined TEA and LCA of an integrated PtL-SAF system.•The MJSP is OPEX intensive due to high electricity consumption.•The WtWa GWP falls below the UK-SAF mandate threshold.•The WtWa ...water footprint of the PtL-SAF is greater than the one of fossil jet fuel.•SAF certificates could help to break-even with the conventional jet fuel.
The current research critically evaluates the technical, economic, and environmental performance of a Power-to-Liquid (PtL) system for the production of sustainable aviation fuel (SAF). This SAF production system comprises a direct air capture (DAC) unit, an off-shore wind farm, an alkaline electrolyser and a refinery plant (reverse water gas shift coupled with a Fischer-Tropsch reactor). The calculated carbon conversion efficiency, hydrogen conversion efficiency, and Power-to-liquids efficiency are 88%, 39.16% and 25.6%, respectively. The heat integration between the refinery and the DAC unit enhances the system's energy performance, while water integration between the DAC and refinery units and the electrolyser reduces the demand for fresh water. The economic assessment estimates a minimum jet fuel selling price (MJSP) of 5.16 £/kg. The process is OPEX intensive due to the electricity requirements, while the CAPEX is dominated by the DAC unit. A Well-to-Wake (WtWa) life cycle assessment (LCA) shows that the global warming potential (GWP) equals 21.43 gCO2eq/MJSAF, and is highly dependent on the upstream emissions of the off-shore wind electricity. Within a 95% confidence interval, a stochastic Monte Carlo LCA reveals that the GWP of the SAF falls below the UK aviation mandate treshold of 50% emissions reduction compared to fossil jet fuel. Moreover, the resulting WtWa water footprint is 0.480 l/MJSAF, with the refinery’s cooling water requirements and the electricity’s water footprint to pose as the main contributors. The study concludes with estimating the required monetary value of SAF certificates for different scenarios under the possible UK SAF mandate guidelines.
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•Effective preservation policy for short-life deteriorating products to improve lifetime.•Adjustable selling-price based on product’s lifetime to improve the demand.•Time-increasing ...and lifetime dependent rate of deterioration.•Nonlinear mathematical modelling and optimization.
Food products deteriorate with time, that affects their freshness and demand. Several preservation policies have been suggested in literature for controlling the deterioration. This research work proposes a supply chain model comprising of a manufacturer and a retailer for deteriorating products with controllable rates of deterioration by improving product’s lifetime (freshness) through preservation in form of storage conditions and delayed ripening agents (preservatives). Customers’ purchasing power controls the purchase quantity; thereby allowing them to buy more products for lower prices and vice versa. This observation is incorporated in this study by considering selling price dependent demand for fresh food items. The proposed model considers a variable (lifetime dependent) component of selling price to integrate consumers’ behavior of buying fresher products for higher prices. The proposed supply chain is presented as a nonlinear mathematical model which is solved by using analytical optimization methods and numerical approaches. Considering the given assumptions, this study explores optimal decision-making for selling price, investment in preservation technology (PT), and cycle time for optimizing product’s freshness, deterioration rate, and demand to maximize the total supply chain profit. The results of the numerical experiments reveal the benefits of the proposed policies by exhibiting significant improvements in product’s freshness, deterioration rate, demand, and profitability. A nexus of the product’s freshness, selling price, and demand is investigated which suggests keeping the total selling price unchanged while improving the demand by increasing freshness through the proposed preservation policy. Some managerial insights are provided for decision-making within food chains.
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.
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We investigate a supply-chain model with a capital-constrained app developer. The developer interacts with a distribution platform via an agency contract, and the demand is uncertain and dependent on ...the app’s quality level and selling price. Given the amount of capital that the developer commits to investing in the creation of quality, the platform offers the developer a loan at a certain interest rate, based on which the developer determines the app’s quality level and subsequently also the selling price. We analytically prove that: (i) the interest rate offered by the platform decreases in the developer’s capital and, interestingly, the platform subsidizes the developer’s efforts either when the platform’s share of the revenue or the developer’s capital are sufficiently large; (ii) there is an amount of capital assigned to the creation of quality that is optimal in terms of maximizing the developer’s expected profit; and (iii) the total channel’s expected profit increases in the developer’s capital, which enables us to propose an improved contract leading to Pareto improvement and full coordination by using a side payment that compensates the developer for his loss of profit. In addition, we compare the supply-chain measures of the platform-financing model with those of four common benchmark models: a self-financing developer, a centralized system, no financing, and bank financing. Finally, we extend the analysis in three directions: setting price under demand uncertainty; analyzing a multiplicative demand form with regard to price and quality; and exploring the case of bank financing in addition to platform financing.
•Modeling an agency contract with capital-constrained developer and platform financing.•Under certain conditions, the platform should subsidize the app’s development.•The developer may not need to invest his entire capital in order to get a subsidy.•The app’s quality, selling price and demand increase with the developer’s investment.•A modified contract can lead to Pareto improvement and full coordination.
The conversion of cellulosic biomass to ethanol as a viable way of decarbonizing the transportation sector has experienced a growing interest in the last few decades. However, this infant industry ...still struggles to succeed commercially. To examine the economic feasibility of cellulosic ethanol, this study conducts a meta-analysis using recently published Techno-Economic Analysis (TEA) studies, which compute the Minimum Fuel Selling Price (MFSP) to measure the economic viability of ethanol production. This review finds that ethanol MFSPs range from $0.90–6.00/gallon with an average of $2.65/gallon, which is comparable to retail gasoline prices in the U.S. The considerable variation in MFSP estimates is due to the wide range of assumptions made by TEA studies. The unit cost of production was computed to examine the economies of scale effect, which resulted in a scale factor of 0.69. This estimate affirms the assumptions made by TEA studies. Multivariate linear regression shows that capital cost is positively correlated, while input capacity and output capacity are negatively correlated, with MFSP. These variables significantly impact MFSP, while pathway, feedstock type, and feedstock cost are not statistically significant due partly to data limitations. Findings from this analysis provide insights for improving the economic viability of cellulosic ethanol, which calls for a suite of government policies including financial incentives, mandates, and assistance programs for this industry to thrive.
•Factors affecting cellulosic ethanol's economic feasibility are studied.•The average minimum fuel selling price is comparable to retail gasoline prices.•A scale-factor of 0.69 is observed in the estimation of plant capital cost.•Input capacity and capital cost affect the economic viability of cellulosic ethanol.•Government policies are important to support this infant industry.
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.
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•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.
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.
This paper considers a profitable heterogeneous vehicle routing problem with cross-docking (PHVRPCD). In the real world, it is not possible to serve all customers and suppliers. Based on the ...purchasing cost and selling price of the products as well as the resource limitation, they will be in the plan only if it is profitable to serve them, so satisfying all demands is not necessary. Cost reduction has been considered in the previous studies as a main objective while neglecting the total profit. In this study, increasing the total profit of a cross-docking system is the main concern. For this purpose, a mixed-integer linear programming (MILP) model is used to formulate the problem mathematically. A new hybrid meta-heuristic algorithm based on modified variable neighborhood search (MVNS) with four shaking and two neighborhood structures and a genetic algorithm (GA) is presented to solve large-sized problems. The results are compared with those obtained with an artificial bee colony (ABC) and a simulated annealing (SA) algorithm. In order to evaluate the performance of the proposed algorithms, various examples of a real data set are solved and analyzed. The computational results reveal that in the small-size test problems, the hybrid algorithm is able to find optimal solutions in an acceptable computational time. Also, the hybrid algorithm needs less computational time than others and could achieve better solutions in large-size instances.
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•A practical version of vehicle routing problem integrated with cross docking is modeled and defined.•Three meta-heuristic algorithms, nam-ely a hybrid GA with modified VNS, ABC and SA are designed to solve large-size problems.•A new heuristic algorithm is developed to generate high quality initial solutions.•Our proposed model and solution methods are evaluated in a set of real-world inspired instances.•It was proved that the proposed hybrid algorithm has acceptable performance and is significantly better than the others in this problem.
We investigated the techno-economic analysis of two integrated torrefaction and pelletization systems: (1) Torrefaction befOre Pelletization and (2) Torrefaction After Pelletization configurations to ...produce torrefied wood pellets. The detailed mass and energy balances and operating parameters were obtained from the process simulation model developed with the base case plant capacity of 100,000 Mg yr−1 using natural gas as an auxiliary fuel source. A discounted cash flow analysis was conducted for both configurations to estimate the capital expenditure, operating expenses, production cost, and the minimum selling price of torrefied pellets. The minimum selling price of torrefied pellets at the plant gate was $207 Mg−1 ($8.5 GJ−1) for the Torrefaction before Pelletization and $197 Mg−1 ($8.1 GJ−1) for the Torrefaction After Pelletization configurations. An increase in the plant capacity of up to 200,000 Mg yr−1 for both configurations decreased the minimum selling price by 10%. The sensitivity analysis of various operational and financial parameters demonstrated that the feedstock cost and torrefaction product yield were the most sensitive parameters influencing the minimum selling price of torrefied pellets. Future opportunities exist to reduce the minimum selling price of torrefied pellets to become competitive to conventional wood pellets and coal.
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