The construction of a composite index for general satisfaction in Turkey and the investigation of its determinants

The goal of public enterprises is to increase the wealth and happiness of individuals. This target lets them make the investment to fulfill these expectations. However, not all citizens in a country might have the same opportunities. This case requires comparing citizens who live in cities with regard to satisfaction levels. This study consists of two stages. In the first stage, a composite index called the General Satisfaction Index (GSI), which aims to explain the satisfaction levels of citizens living in cities, is obtained by using the Benefit of the Doubt method. Contrary to the previous studies, the satisfaction indicators based on the emotions and senses of citizens are used to construct a composite index. Satisfaction indicators’ contribution to GSI is ensured using the minimum weights. In the second stage of this study, socioeconomic determinants of GSI are investigated in both countrywide and regions by using regularized regression methods. In the result of the regression analyze, it is confirmed that there are different socioeconomic determinants of satisfaction levels for countrywide and each region. For this reason, it is proposed that policymakers should follow different politicizes in each region to increase the satisfaction levels of citizens in the country.     

制度距离、投资动机与企业OFDI区位选择——中国对外直接投资“制度风险偏好”的一种解释

由于企业的对外直接投资（OFDI）存在制度适应成本，东道国与母国之间的制度距离会对企业OFDI产生负向影响。基于2003—2015年中国对140个国家和地区OFDI的分析表明：中国企业的OFDI具有明显的市场寻求动机和战略资源寻求动机，其中，市场寻求型OFDI表现出显著的互补效应，战略资源寻求型OFDI表现出一定程度的挤出效应；东道国与中国的制度距离会通过投资动机影响中国企业OFDI的区位选择，即倾向于向制度距离较小的国家和地区进行OFDI，且制度距离会弱化市场寻求型OFDI的互补效应和战略资源寻求型OFDI的挤出效应。站在企业角度来看，中国企业在进行OFDI时并不具有“制度风险偏好”，而是表现出“制度风险规避”特征：选择对其自身发展来讲制度风险较小（制度距离较小）的目标市场进行OFDI。因此，中国应深化市场经济体制改革，提升国内制度质量，加强国际经济合作，并增强企业的制度适应能力，以有效减小制度距离对企业OFDI区位选择的约束，进而优化OFDI区位分布，提高OFDI效益和质量。     

Optimal capacity and operation design of a robot logistics system for the hotel industry

This study introduces an optimal capacity and operation design of a robot logistics system that can reduce human workload in the hotel industry. In hotels, there are several duties that can be replaced by robots such as accompanying guests to the certain areas, delivering specific items to the guest rooms, and transporting some items that guests want to be removed from the guest rooms. To apply the robot logistics system in the hotel industry, the capacity and operation design should be prepared adequately. For that, a mathematical model-based optimization technique is used to decide the number of robots with the concept of minimizing total investment cost and to derive the optimal job assigning with the purpose of maximizing total covered jobs. In addition, a numerical example is performed to validate the proposed mathematical model and the sensitivity tests are examined to reflect the random features.     

基于改进Dijkstra算法的最短路算法

Dijkstra算法是求解最短路径问题的经典算法。在现如今的城市交通网络中,经常需要寻求两个地点之间的最短距离,减少运输时间。本文将Dijkstra算法与C语言相结合,对Dijkstra算法进行改进,根据实际网络图的情况,建立了相应的数学模型,运用C语言编程,在给定的网络图中,实现了只需确定起始点和终点,就可以直接输出最短路径和最短距离的功能。在有多个相同最短路径的情况下,会将多个最短路径一起输出,在搜索到终点时,立即跳出,结束循环。在一般情况下,无需对所有点进行迭代,提高了效率。这种方法可以应用到现在的物流运输中,以此来节约时间,降低成本。     

疫情对经济的影响与“灾害适应型经济”的转型

新型冠状病毒肺炎疫情对中国乃至世界经济产生了巨大的冲击。疫情的冲击颠覆了传统经济学的认知，需从理论上对经济衰退的原因和机制重新认识，特别是对疫情之下“非常态经济”及其与“常态经济”之间的关系加以研究；疫情的冲击亦暴露出现有的经济系统存在的问题，需要推动经济的转型，打造“灾害适应型经济”。本文基于辩证思想，从负面和正向两个方面来研究疫情对经济的影响，充分发掘新动能，利用新机会，推动中国经济向“灾害适应型经济”转型，实现中国经济的可持续、高质量发展。     

基于SBO-PP模型的水资源可持续发展能力评价模型及应用

为利用投影寻踪(PP)技术科学,客观评价区域水资源可持续发展能力,基于生态环境、水资源和经济社会因素选取20个指标构建区域水资源可持续发展能力评价指标体系。利用新型仿生群体智能算法——凉亭鸟优化(SBO)算法优化PP技术最佳投影方向,提出SBO-PP水资源可持续发展能力评价模型,并构建灰狼优化(GWO)算法-PP模型、人工蜂群(ABC)算法-PP模型、差分进化(DE)算法-PP模型、地理生物学优化(BBO)算法-PP模型、粒子群优化(PSO)算法-PP模型作对比,以云南省2006—2015年及2020年水资源可持续发展能力评价为例进行实例研究。结果表明:SBO算法优化PP技术获得的适应度值优于GWO、ABC、DE、BBO和PSO算法,具有较好的求解精度、稳健性能和极值寻优能力。SBO-PP模型对云南省2006—2007年水资源可持续发展能力评价为"较差",2008—2015年评价为"中等",2020年评价为"较强"。     

A genetic algorithm based approach to transactional and QoS-aware service selection

As there are various risks of failure when Web services are deployed in unreliable environment, the execution of a composite Web service (CWS) requires the transaction mechanism to guarantee its reliable execution. However, the existing service selection approaches consider QoS and transaction separately and have not considered that transactional properties may affect the QoS such as the execution time of a CWS. This work addresses the importance of considering transactional properties and how the transactional properties affect the QoS simultaneously in the process of service selection by a QoS-aware and transactional-aware selection approach. First, a performance evaluation method is proposed to calculate the execution time of a transactional CWS. Then, a genetic algorithm based approach, which takes into account the execution time, price, transactional property and successful execution rate of CWS, is presented to achieve global optimisation service selection. Finally, experimental results show the efficiency and effectiveness of the approach.     

Structured deplaning via simulation and optimization

Deplaning naturally occurs row by row down the length of an aircraft. Using simulation and optimization, we design deplaning strategies (e.g., deplane by group and/or column) that significantly reduce the overall unstructured deplaning time. The evaluations derived from a combination of optimization and simulation were tested across several equipment types using data gathered through field observations for calibration.     

Design and development of inventory knowledge discovery system

Inventory management (IM) performance is affected by the forecasting accuracy of both demand and supply. In this paper, an inventory knowledge discovery system (IKDS) is designed and developed to forecast and acquire knowledge among variables for demand forecasting. In IKDS, the TREes PArroting Networks (TREPAN) algorithm is used to extract knowledge from trained networks in the form of decision trees which can be used to understand previously unknown relationships between the input variables so as to improve the forecasting performance for IM. The experimental results show that the forecasting accuracy using TREPAN is superior to traditional methods like moving average and autoregressive integrated moving average. In addition, the knowledge extracted from IKDS is represented in a comprehensible way and can be used to facilitate human decision-making.     

Estimation of interregional input–output table using hybrid algorithm of the RAS method and real-coded genetic algorithm

In this paper, we propose a method for improving the accuracy of the estimation of interregional input–output tables, by combining the RAS method and the real-coded Genetic Algorithm (GA); these are simple representative methods for the estimation of an interregional input–output table. By comparing the performance evaluation results obtained using the proposed method, the RAS method, and Simulated Annealing, we verified that the combination of the genetic algorithm and the RAS method can enhance the estimation accuracy of an interregional input–output table. In addition, performance is further enhanced by adjusting GA parameters.