Selection of expert system shells for traffic signal design

Although the use of expert systems (ESs) as a problem-solving tool is relatively new in the transportation profession, it has been recognized that a well-designed ES can contribute in areas where the knowledge domain requires an integration of expertise from various disciplines or is very complex and difficult to quantify. To minimize the effort involved in developing essential ES mechanisms, researchers often prefer to use ES shells which provide a standard inference procedure, knowledge representation, and a user-friendly design environment. However, commercial ES shells tend to be designed for only certain classes of problems, and are not as general and flexible as programming languages. More than 150 commercial ES shells are available in the microcomputer market. Most ES shells are usually claimed by their vendors to be usable for almost any conceivable applications, but such claims have often proved to be extravagant. Hence, the selection of an efficient yet costeffective commercial shell is one of the most critical tasks in ES development. In reviewing the vital task of ES shell selection, this paper presents our experience in evaluating more than 30 ES shells for developing an ES for signal design. The proposed ES includes signal settings, phasing plans, controllers, and detector locations.     

An Epsilon Bargaining Game-Theoretic Formulation Between Carrier and Container Terminal Operators for Servicing Vessels During Unloading Operations

Due to globalization trends and the increasing competition between ports, the maritime policy for container shipments has witnessed a change in operations that resulted in less reliance on direct freight flows and higher transshipment operations. Motivated to investigate a soft intelligent decision-making approach using game theory in the context of servicing vessels during unloading operations in transshipment, we propose an epsilon bargaining approach between the carrier and the container terminal operator (CTO). The objective of the game is to maximize the carrier service level while minimizing operation costs for the CTO. The players' utilities, which depend on the service level and the fees for the carrier, as well as the revenues generated and the cost incurred for the CTO, are uniquely formulated and evaluated in a bargaining scenario using an ordinal ranking approach. The negotiation process is further improved between the two players based on our proposed Epsilon Bargaining Equilibrium, which to the best of our knowledge has not been used in maritime transportation problems. Results from a risk aversion case illustrate the value of the soft computing mathematical model that we formulated and motivate follow-up research.     

基于简化DPCNN的最短路径算法

传统求解最短路径（SP）问题的方法一般有组合技术与代数方法2大类,但算法复杂度的指数上界为2．376,不能实时对大规模SP问题进行求解。文中提出1种简化的时延脉冲耦合神经网络（SDPCNN）模型,可1次求解源点到其他所有点的最短路径,算法时间复杂度仅有O（n）．实验证实了这一模型的有效性,且计算时间仅为未简化模型的5％～10％。