China’s Urbanization Process and Outlook~

Starting JPom a low level China＇s rapid urOamzatlon ttas talcen on a targe scale over the past three decades. The urbanization of urban clusters has become a key driver of China＇s economic development. However, China＇s urbanization has been confronted with many issues, such as high resource and environmental costs, low level of citizenship for migrant workers, strong economic polarization and excessive dependence on land encroachment. In the near future, China＇s urbanization will enter a period of strategic transitioning, and the enhancement of the quality of urbanization will become a strategic priority. China＇s urbanization rate is projected to reach 60% by 2020 and 68% by 2030, eventually exceeding 80% by 2050. China＇s future urbanization must proceed from local realities, promote the balanced development of small, medium-sized and large cities and towns, optimize the spatial layout of urbanization, and follow a sensible pattern.

“纸上谈兵”与项目管理

“纸上谈兵”一般被人们用来形容只会夸夸其谈、不切实际的人。不过有时候,“纸上谈兵”也能帮你解决问题。下面,我们就来看看项目管理中的“纸上谈兵”。

ICN Based Vehicle-to-Cloud Delivery for Multimedia Streaming in Urban Vehicular Networks

Mobile multimedia streaming is an open topic in vehicular environment. Due to the high intermittent links, it has become a critical challenge to deliver high quality video streaming in vehicular networks. In this paper, we reform the Information Centric Networking （ICN） concept for multimedia delivery in urban vehicular networks. By leveraging the 1CN perspective, we highlight that vehicular peers can obtain multimedia chunks via the vehicle-to-cloud （V2C） approach to improve the delivery quality. Based on this, we propose a lightweight multipath selection strategy to guide the network system to adaptively adjust the forwarding means. Extensive simulations show that the proposed solution can optimize the utilization of network paths, lighten network loads as well as avoid wasting resources.

Multi-criterion system optimization model for urban multimodal traffic network

In this paper,computational models of environmental pollution and energy consumption of urban multimodal traffic network are proposed according to pertinent research and a multi-objective programming model is then developed to formulate optimization problem for such a system.Simultaneously,the main factors,such as travel time,pricing and convenience which influence travelers' choice behaviors are all considered and a combined assignment model is proposed to simulate travelers' mode and route choices.A bi-level programming model,in which the multi-objective optimization model is treated as the upper-level problem and the combined assignment model is processed as the lower-level problem,is then presented to solve multi-criterion system optimization problem for urban multimodal traffic network.The solution algorithms of the proposed models are also presented.Finally,the model and its algorithms are illustrated through a simple numerical example.

Multi-Objective Optimization of Urban Bus Network Using Cumulative Prospect Theory

Multi-objective optimization of urban bus network can help improve operation efficiency of the transit system and develop strategies for reducing urban traffic congestion in China. The work used cumulative prospect theory, currently the most influential model for decision under uncertainty,to optimize urban bus network. To achieve the research objective, the work developed the theoretical framework of urban bus network optimization, including optimization principle, optimization objectives and constraints. Furthermore, optimization objectives could comprehensively reflect expectations of passengers and bus companies from the dimension of time, space and value. It is more scientific and reasonable compared with only one stakeholder or dimension alone in the previous studies. In addition,the technique for order preference by similarity to ideal solution(TOPSIS) was used to determine the positive and negative ideal alternative. The correlations between the optimization alternatives and the ideal alternatives were estimated by grey relational analysis simultaneously. The cumulative prospect theory(CPT) was used to determine the best alternative by comparing comprehensive prospect value of every alternative, accurately describing decision-making behavior compared with expected utility theory in actual life. Finally, Case of Xi'an showed that the method can better adjust the bus network,and the optimization solution is more reasonable to meet the actual needs.