The effect of amelioration can be generally observed in growing items such as livestock. As a result of this effect, the value and stock of these items gain over time. However, a decline in the inventory of these items is also observed due to deterioration. In this research work, an inventory model is studied for ameliorating items considering the effects of green and preservation technologies under an advance payment policy. The retailer invests in preservation techniques to control the deterioration effect on items. Moreover, the retailers also invest in green technologies to reduce carbon emissions emitted during the stocking period of these growing items. It is considered that the demand for the items is dependent on advertisement frequency, selling price, and stock level. The objective is to obtain the optimal frequency of advertisement, preservation technology investment, green technology investment, selling price, and time of occurrence of zero inventory level that maximize the total profit per unit time. The optimal values of the decision variables are obtained using an algorithm with the help of software Mathematica. Several solved numerical examples are presented, while sensitivity analysis is performed for different parameters. An increase in the demand increases the profit of the retailer. The retailer increases the investment in green technology for any increase in the carbon tax. Furthermore, a shorter duration of advance payment and a smaller number of equal prepayments increase the retailer’s profit. Numerical results indicate that investments in green and preservation technologies result in higher profit for the retailer.
China has recently raised its ambition to reduce non-CO2 greenhouse gases (NCGGs) emissions. However, China’s current mitigation policy framework for NCGGs is still evolving and is far from the requirements for achieving the 2035 NDCs. In response, this study summarizes China’s mitigation measures and their impacts from the existing literature, with the objective of facilitating a quick understanding of the overall status of NCGGs mitigation in China and informing actions. Based on Web of Science, the relevant literature falls into two categories: (1) emission inventory and drivers and thus mitigation measures; (2) impact assessment of mitigation measures. Our review shows that NCGGs emissions inventory has been conducted across multiple scales— national, provincial, prefectural, and facility level—but focuses primarily on methane and nitrous oxide. Previous studies documented super-emitters, seasonal patterns, and spatial clustering in China’s NCGGs emissions. Mitigation measures in areas such as rice cultivation, farmland management, livestock manure management, and coal mining have been extensively examined. Management-based measures often demonstrate high cost–benefits, including low cost, high mitigation efficiency, and yield improvement. Technology-based measures achieve higher mitigation efficiency but face considerable cost. The study also discusses the research progress of mitigation policy mixes. Future research should prioritize addressing research gaps related to fluorinated gases, clarifying mitigation responsibility, exploring market-based mitigation policies, and joint mitigation of multiple greenhouse gases.
Under the combined impetus of the International Maritime Organization’s greenhouse gas reduction strategy, the European Union’s FuelEU Maritime initiative, and China’s dual-carbon goals, the shipping industry is accelerating its transition toward alternative fuels. Yet prevailing evaluation approaches are largely static and thus ill-suited to the dynamic uncertainties that characterize technological progress, economic conditions, and policy regimes. To address this gap, this study develops a dynamic multi-criteria decision-making framework capable of conducting intertemporal and cross-scenario assessments. A dynamic fuzzy matter‑element model is proposed for the comprehensive assessment of six principal alternative marine fuels—liquefied natural gas (LNG), methanol, ammonia, hydrogen, biofuels, and batteries. The evaluation framework is structured around six dimensions, namely technology readiness, safety, life‑cycle environmental performance, economics, supply‑chain maturity, and the fuel flexibility index. By incorporating time-evolving indicator values, scenario-driven dynamic weights, and trapezoidal membership functions, the model quantifies each fuel’s degrees of membership across graded performance levels. The study corroborates a long-term multi-fuel coexistence equilibrium in maritime decarbonization, with no single solution universally optimal across scenarios. The proposed dynamic fuzzy matter-element model offers decision-makers an effective quantitative instrument for crafting robust fuel-transition strategies under uncertainty. Methodologically, the research integrates temporal dynamics into fuzzy matter-element theory and introduces composite indicators such as the fuel flexibility index, thereby furnishing a novel analytical lens and decision support for charting green transition pathways in the shipping sector.
Path planning problems often involve multiple constraints that cannot always be simultaneously satisfiable in practice. Existing approaches focus on eliminating conflicts to restore feasibility, as they implicitly assume that conflict-free solutions exist. However, when constraints are inherently infeasible, these methods provide limited guidance in generating solutions. To address this limitation, we shifted path planning problems to minimum-violation optimization problems, where shift vectors are integrated into the objective function. Then, we proposed a minimum-violation optimization method that integrates Monte Carlo Tree Search with the augmented Lagrangian method, explicitly quantifying constraint violations by strongly convex measures. We further derived the method’s convergence rate and error bound, and validated it on benchmark instances of the Chinese Postman Problem with conflict constraints. In addition, we investigated the use of large language models as auxiliary components in the simulation phase and examined the conditions under which they are effective.
