优网通即将推出IC教育训练平台──访优网通国际资讯有限公司董事长杨丁元先生和中国区副总王伯华先生

据中国电子信息产业发展研究院提供的资料显示，到2005年，我国IC产量将达到200亿快，销售额将达到90亿美元。如果按照IC产值与IC工程师需求量的通常比率来计算，那么到2005年，我国IC工程师的需求量约为30000名。我国目前仅有4600名IC工程师，而我国教育系统目前每年只能提供2000多名IC工程师，可见IC设计人才真是奇货可居。“在大中华半导体产业中、下游产业的带动下，IC设计业近来发展迅速，学校毕业的人才已供不应求，人才荒将是限制IC产业发展的关键因素，培养专业的IC设计人才是市场的当务之急。”

Joint Optimization on Energy and Delay for Target Tracking in Internet of Things

Network and communications models are built for target tracking and pursuing in the Internet of Things (IoT).According to these models,two tracking schemes which jointly optimize the pursuing energy and delay are proposed.The merits of these schemes are that they can enhance energy efficiency of both the pursuing route and communication in the network.Moreover,experimental results are provided to demonstrate the benefits of the proposed schemes which will be used as optimization schemes for the IoT tracking service.

Hybrid genetic algorithm for the optimization of mine ventilation network

Used genetic algorithm (GA) to optimize the network of ventilation in order toavoid artificial convergence and speed up the convergence rate to introduce the Powellalgorithm. The Powell algorithm had been integrated into GA. Powell had the effectivecapacity of solving the local optimal solution. Powell and the cross as a method ofchoice, a variation of the parallel operator, can be a better solution to the prematureconvergence of the GA problem. The two methods will be improved to make it an effective combination of hybrid GA called hybrid genetic algorithm (HGA) for the introductionof mine ventilation network optimization and to be used to solve the problem of regulating mine optimization.

Allocation optimization of bicycle-sharing stations at scenic spots

Bicycle-sharing system is considered as a green option to provide a better connection between scenic spots and nearby metro/bus stations. Allocating and optimizing the layout of bicycle-sharing system inside the scenic spot and around its influencing area are focused on. It is found that the terrain, land use, nearby transport network and scenery point distribution have significant impact on the allocation of bicycle-sharing system. While the candidate bicycle-sharing stations installed at the inner scenic points, entrances/exits and metro stations are fixed, the ones installed at bus-stations and other passenger concentration buildings are adjustable. Aiming at minimizing the total cycling distance and overlapping rate, an optimization model is proposed and solved based on the idea of cluster concept and greedy heuristic. A revealed preference/stated preference （RP/SP） combined survey was conducted at Xuanwu Lake in Nanjing, China, to get an insight into the touring trip characteristics and bicycle-sharing tendency. The results reveal that 39.81% visitors accept a cycling distance of 1-3 km and 62.50% respondents think that the bicycle-sharing system should charge an appropriate fee. The sttrvey indicates that there is high possibility to carry out a bicycle-sharing system at Xuanwu Lake. Optimizing the allocation problem cluster by cluster rather than using an exhaustive search method significantly reduces the computing amount from O（2^43） to O（43 2）. The 500 m-radius-coverage rate for the alternative optimized by 500 m-radius-cluster and 800 m-radius-cluster is 89.2% and 68.5%, respectively. The final layout scheme will provide decision makers engineering guidelines and theoretical support.

An optimized control of ventilation in coal mines based on artificial neural network

According to the nonlinear and time dependent features of the ventilation systems for coal mines, a neural network method is applied to control the ventilator for coal mines in real time. The technical processes of coal mine ventilation system are introduced, and the principle of controlling a ventilation fan is also explained in detail. The artificial neutral network method is used to calculate the wind quantity needed by work spots in coal mine on the basis of the data collected by the system, including ventilation conditions, environmental temperatures, humidity, coal dust and the contents of all kinds of poisonous and harmful gases. Then the speed of ventilation fan is controlled according to the required wind which is determined by an overall integration of data. A neural network method is presented for overall optimized solution or the genetic algorithm of simulated annealing.

Simultaneous optimization of transit network and public bicycle station network

The traditional manner to design public transportation system is to sequentially design the transit network and public bicycle network. A new public transportation system design problem that simultaneously considers both bus network design and public bicycle network design is proposed. The chemical reaction optimization(CRO) is designed to solve the problem. A shortcoming of CRO is that, when the two-molecule collisions take place, the molecules are randomly picked from the container.Hence, we improve CRO by employing different mating strategies. The computational results confirm the benefits of the mating strategies. Numerical experiments are conducted on the Sioux-Falls network. A comparison with the traditional sequential modeling framework indicates that the proposed approach has a better performance and is more robust. The practical applicability of the approach is proved by employing a real size network.

Genetic Algorithm-Based Redundancy Optimization Method for Smart Grid Communication Network

This paper proposes a redundancy optimization method for smart grid Advanced Metering Infrastructure(AMI) to realize economy and reliability targets.AMI is a crucial part of the smart grid to measure,collect,and analyze data about energy usage and power quality from customer premises.From the communication perspective,the AMI consists of smart meters,Home Area Network(HAN) gateways and data concentrators;in particular,the redundancy optimization problem focus on deciding which data concentrator needs redundancy.In order to solve the problem,we first develop a quantitative analysis model for the network economic loss caused by the data concentrator failures.Then,we establish a complete redundancy optimization model,which comprehensively consider the factors of reliability and economy.Finally,an advanced redundancy deployment method based on genetic algorithm(GA) is developed to solve the proposed problem.The simulation results testify that the proposed redundancy optimization method is capable to build a reliable and economic smart grid communication network.

A Combined Admission and Priority Control Mechanism for Assuring Communication Quality in VANETs integrated with Wireless Mesh Networks

In this paper, we introduce a new combined priority and admission control mechanism applying in the VCN （Vehicular Communication Network） which is designed with an integration of the Vehicular Ad-hoc Networks （VANETs） based on standard IEEE 802.11 p and IEEE 802.11 s WMNs （Wireless Mesh Networks）. Simulation experiments are intensively investigated to evaluate the novel combined priority and admission control mechanism to assure quality of the I2V （Infrastructure to Vehicle） emergency services occurred during the time video flows are being delivered between content servers and cars. The simulation results show effectiveness of proposed priority and admission control schemes in term of the minimized end-to-end delay as well as the increase of throughput and PDR （Packet Delivery Ratio） of the emergency data flow.

Optimal paths planning in dynamic transportation networks with random link travel times

A theoretical study was conducted on finding optimal paths in transportation networks where link travel times were stochastic and time-dependent(STD). The methodology of relative robust optimization was applied as measures for comparing time-varying, random path travel times for a priori optimization. In accordance with the situation in real world, a stochastic consistent condition was provided for the STD networks and under this condition, a mathematical proof was given that the STD robust optimal path problem can be simplified into a minimum problem in specific time-dependent networks. A label setting algorithm was designed and tested to find travelers' robust optimal path in a sampled STD network with computation complexity of O(n2+n·m). The validity of the robust approach and the designed algorithm were confirmed in the computational tests. Compared with conventional probability approach, the proposed approach is simple and efficient, and also has a good application prospect in navigation system.

Model and algorithm of optimizing alternate traffic restriction scheme in urban traffic network

An optimization model and its solution algorithm for alternate traffic restriction(ATR) schemes were introduced in terms of both the restriction districts and the proportion of restricted automobiles. A bi-level programming model was proposed to model the ATR scheme optimization problem by aiming at consumer surplus maximization and overload flow minimization at the upper-level model. At the lower-level model, elastic demand, mode choice and multi-class user equilibrium assignment were synthetically optimized. A genetic algorithm involving prolonging codes was constructed, demonstrating high computing efficiency in that it dynamically includes newly-appearing overload links in the codes so as to reduce the subsequent searching range. Moreover,practical processing approaches were suggested, which may improve the operability of the model-based solutions.

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.