Strategic planning for the optimal distribution of COVID-19 vaccines.

This work presents a multi-objective optimization strategy for fair vaccine allocation through different fairness schemes. The proposed approach considers a diverse series of parameters related to different public health data and social behaviors that influence the correct distribution of vaccines, such as corruption and crime. Simultaneously, the formulation includes prioritizing those groups with the highest risk based on the epidemiological traffic light. Furthermore, the presented strategy involves different budget constraints that allow identifying trade-off solutions through Pareto fronts. Therefore, vaccine allocations are obtained by combining fairness concepts with multi-objective optimization. The applicability of the model is illustrated using the case study of Mexico. The solution to the proposed scenarios was carried out using different justice schemes and an economic objective function. The results show the compromises between a satisfaction index and costs, which are shown through Pareto optimal solutions that allow selecting the solutions that balance the objectives. The solutions provided by the social welfare scheme suggest a greater allocation of vaccines to those states with higher epidemiological risk, which may be helpful in the first stage of vaccination. On the other hand, the Rawlsian scheme provides more balanced solutions that can be useful in situations with lower rates of infection. Finally, the Nash scheme is the one that provides the most balanced solutions, favoring to a lesser extent the areas with the highest epidemiological risk, which may be useful in the later stages of vaccination.

Maximum Efficient Power Performance Analysis and Multi-Objective Optimization of Two-Stage Thermoelectric Generators.

Two-stage thermoelectric generators have been widely used in the aerospace, military, industrial and daily life fields. Based on the established two-stage thermoelectric generator model, this paper further studies its performance. Applying the theory of finite-time thermodynamics, the efficient power expression of the two-stage thermoelectric generator is deduced firstly. The maximum efficient power is obtained secondly by optimizing the distribution of the heat exchanger area, distribution of thermoelectric elements and working current. Using the NSGA-II algorithm, multi-objective optimizations of the two-stage thermoelectric generator are performed thirdly by taking the dimensionless output power, thermal efficiency and dimensionless efficient power as objective functions, and taking the distribution of the heat exchanger area, distribution of thermoelectric elements and output current as optimization variables. The Pareto frontiers with the optimal solution set are obtained. The results show that when the total number of thermoelectric elements is increased from 40 to 100, the maximum efficient power is decreased from 0.308W to 0.2381W. When the total heat exchanger area is increased from 0.03m2 to 0.09m2, the maximum efficient power is increased from 0.0603W to 0.3777W. The deviation indexes are 0.1866, 0.1866 and 0.1815 with LINMAP, TOPSIS and Shannon entropy decision-making approaches, respectively, when multi-objective optimization is performed on three-objective optimization. The deviation indexes are 0.2140, 0.9429 and 0.1815 for three single-objective optimizations of maximum dimensionless output power, thermal efficiency and dimensionless efficient power, respectively.

Impacts of haze pollution on China's tourism industry: A system of economic loss analysis.

Haze pollution not only negatively influences public health but also causes great economic losses. However, most previous studies have mainly focused on health-related economic losses, while the negative effects of haze pollution on the tourism industry are often ignored, leading to the unsustainable development of tourism. In this context, contrasting with previous research perspectives, this article selected several representative tourist cities from East China, South China, Central China, North China, Northwest China, Southwest China, and Northeast China as research objects in an empirical study, developing an economic loss analysis system to quantitatively evaluate the losses in the tourism industry caused by haze pollution. This system uses the satin bower bird optimization-based distribution estimation method to identify the optimal distribution of haze pollution, demonstrating superior performance to the traditional estimation method. Meanwhile, the optimal distribution of haze pollution is employed to measure the probability of different concentration limits in each area. Furthermore, the economic loss formula of the tourism industry is proposed in the devised system, calculating the economic loss caused by haze pollution at different degrees. The results show that haze pollution in different degrees has caused varying degrees of losses to China's tourism industry. In terms of seasonality and regionality, different seasons and different regions produce different results. Compared with summer, autumn and winter haze pollution is more severe, creating obvious seasonal differences. There is also a regional agglomeration effect, whereby the regional distribution of haze pollution is consistent with each region's economic development.

Optimal distribution of the fundamental non-efficient load current terms between the energy gateways connected in grid-tied microgrids.

Main objective of this paper is the optimal distribution of the fundamental non-efficient load current terms between the inverters -Energy Gateways (EGs)- connected in grid-tied microgrids (MGs). The main feature of the presented approach is the use of the EGs as controlled current sources that can compensate fundamental non-efficient load current terms in addition to the generation of fundamental positive-sequence active current, avoiding the use of shunt active power filters. The approach relies on the so-called System of Constant References (SoCR) that is based on the symmetrical components decomposition and dq0 transformation. SoCR procedure decouples efficient and non-efficient components of the instantaneous load currents, transforming all of them into six constant references. The optimization algorithm uses a new approach for the calculation of the peak currents in each phase, avoiding non-convex problems when determining the currents of the EGs considering their operating limits. A medium-power size MG that includes photovoltaic and wind generators, as well as, a battery energy storage system is considered to evaluate the capabilities of the proposal. There were evaluated four scenarios: baseline, balanced distribution, proportional distribution, and optimal distribution. All scenarios, except optimal distribution scenario, surpass the current limits for the EGs connected. The results highlight the benefits of using the EGs as active agents in MG efficient operation and demonstrate how the optimization approach achieves the goal of maintaining the generation capabilities of EGs at the same time that compensates the non-efficient current terms demanded by the load.

Optimization of Functionally Graded Structural Members by Means of New Effective Properties Estimation Method.

An innovative method of effective composite mechanical properties estimation is applied to optimize the distribution of reinforcement in a functionally graded structural element. The concept is based on the assumption of the mechanical equivalence between two configurations: The real heterogeneous composite configuration and the fictitious quasi-homogeneous one. It allows to obtain the analytical formulae describing the dependence of the effective elastic composite properties on the volume fraction of reinforcing inclusions. As an example of application, a circular bar subjected to torsion is considered.