An improved grey wolf optimizer algorithm for identification and location of gas emission

Identification of the leakage of hazardous gases plays an important role in the environment protection, human health and safety of industry production. However, lots of current optimization algorithms, such as particle swarm optimization (PSO) and Grey Wolf Optimizer (GWO), suffer from poor global optimization capability and estimation accuracy. In this work, a hybrid differential evolutionary and GWO (DE-GWO) algorithm is proposed. Tested by simulation cases and Prairie Grass emission experimental data, DE-GWO shows higher estimation accuracy than GWO. Compared with the other four optimization algorithms, DE-GWO exhibits finer robust stability under different population sizes, fewer iterations, as well as higher estimation accuracy with fewer search agents. Importantly, simulation results demonstrate that DE-GWO is more suitable to apply in the scene with a small number of sensors. Therefore, the proposed in this paper outperforms other optimization algorithms for the gas emission inverse problem. DE-GWO can provide reliable estimation towards gas emission identification and positioning, which shows huge potential as the data analysis module of real-time monitoring and early warning system.     

Based on material flow analysis: Value chain analysis of China iron resources

Iron is an important basic resource for national economic development in China. It is of great strategic importance for the sustainable development of China's economy to study the utilization and circulation status of iron resources. In this paper, using the material flow and value chain analysis method, we quantitatively analyzed the value flow of iron resources in China. According to the value chain and price theory of element M, a value stream diagram of iron resources corresponding to the substance flow chart was plotted. Based on the previous material flow analysis result of iron resources, the diagram quantitatively depicted the value of the circulating flow of iron resources in China in 2011. The results show that by recycling materials, the value of the circulating flow of iron resources can bring considerable economic benefits to both producers and consumers. In the production stage, the expenditures of the entire economic system was reduced by 91.77 billion RMB by circulating iron and the income increased by 95 billion RMB by recycling home scrap, which was generated in the crude steel production stage. In the use stage of iron and steel products, the recycling of old scrap enabled the entire economic system to recover 370.78 billion RMB. It should be noted that analysis within a single framework of physical and economic characteristics of iron resources in the economic system can further extend the research chain of substance flow and value flow at the macro level, enhancing the economic value of substances flow research. In addition, by tracking and depicting the value flow cycle of elements, the improvement potentials and the value situations can be determined to provide useful information for conducting processing and technological innovation for waste minimization.     

Socially optimal and fund-balanced advanced recycling fees and subsidies in a competitive forward and reverse supply chain

Advanced recycling fees (ARFs) and government subsidy fees are important for curtailing the consumption of new products and encouraging recycling and disposal of end-of-life (EOL) products. We introduce a model consisting of a leader (the Environmental Protection Agency, EPA) and two groups of followers (MIS firms and recyclers) consisting of manufacturers, importers and sellers, and recyclers which compete in both consuming and recycling markets. The EPA determines the ARFs paid by the MIS firms and the fees subsidizing recyclers to maximize the social welfare in closed-loop supply chains where the MIS firms and recyclers attempt to maximize their respective profit functions. To compare with current practice, we describe a conceptual fund balance model to determine the ARF and subsidy fee on the basis of the balance between total collected ARFs and expenditure of subsidies. Using numerical examples for the laptop computer market in Taiwan, we demonstrate that our results outperform the current practice.