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This paper looks at the first and second best jointly optimal toll and road capacity investment problems from both policy
and technical oriented perspectives. On the technical side, the paper investigates the applicability of the constraint cutting
algorithm for solving the second best problem under elastic demand which is formulated as a bilevel programming problem. The
approach is shown to perform well despite several problems encountered by our previous work in Shepherd and Sumalee (Netw.
Spat. Econ., 4(2): 161–179, 2004). The paper then applies the algorithm to a small sized network to investigate the policy implications of the first and second
best cases. This policy analysis demonstrates that the joint first best structure is to invest in the most direct routes while
reducing capacities elsewhere. Whilst unrealistic this acts as a useful benchmark. The results also show that certain second
best policies can achieve a high proportion of the first best benefits while in general generating a revenue surplus. We also
show that unless costs of capacity are known to be low then second best tolls will be affected and so should be analysed in
conjunction with investments in the network.
Andrew Koh Prior to joining the Institute for Transport Studies in December 2005, Andrew was employed for number of years as a consultant in highway assignment modelling. He is an economist with wide ranging research interests in transport economics as well as evolutionary computation heuristics such as genetic algorithms, particle swarm optimisation and differential evolution. Simon Shepherd At the Institute for Transport Studies since 1989, he gained his doctorate in 1994 applying state-space methods to the problem of traffic responsive signal control in over-saturated conditions. His expertise lies in modelling and policy optimisation ranging from detailed simulation models through assignment to strategic land use transport models. Recently he has focussed on optimisation of road user charging schemes and is currently working on optimal cordon design and system dynamics approaches to strategic modelling. Agachai Sumalee Agachai is currently an Assistant Professor at Department of Civil and Structural Engineering, Hong Kong Polytechnic University (). He obtained a Ph.D degree with the thesis entitled “Optimal Road Pricing Scheme Design” at Leeds University in 2004. His research areas cover transport network modeling and optimization, stochastic network modeling, network reliability analysis, and road pricing. Agachai is currently an associate editor of Networks and Spatial Economics. 相似文献
Agachai SumaleeEmail: |
Andrew Koh Prior to joining the Institute for Transport Studies in December 2005, Andrew was employed for number of years as a consultant in highway assignment modelling. He is an economist with wide ranging research interests in transport economics as well as evolutionary computation heuristics such as genetic algorithms, particle swarm optimisation and differential evolution. Simon Shepherd At the Institute for Transport Studies since 1989, he gained his doctorate in 1994 applying state-space methods to the problem of traffic responsive signal control in over-saturated conditions. His expertise lies in modelling and policy optimisation ranging from detailed simulation models through assignment to strategic land use transport models. Recently he has focussed on optimisation of road user charging schemes and is currently working on optimal cordon design and system dynamics approaches to strategic modelling. Agachai Sumalee Agachai is currently an Assistant Professor at Department of Civil and Structural Engineering, Hong Kong Polytechnic University (). He obtained a Ph.D degree with the thesis entitled “Optimal Road Pricing Scheme Design” at Leeds University in 2004. His research areas cover transport network modeling and optimization, stochastic network modeling, network reliability analysis, and road pricing. Agachai is currently an associate editor of Networks and Spatial Economics. 相似文献
174.
The available highway alignment optimization algorithms use the total cost as the objective function. This is a single objective optimization process. In this process, travel‐time, vehicle operation accident earthwork land acquisition and pavement construction costs are the basic components of the total cost. This single objective highway alignment optimization process has limited capability in handling the cost components separately. Moreover, this process cannot yield a set of alternative solutions from a single run. This paper presents a multi‐objective approach to overcome these shortcomings. Some of the cost components of highway alignments are conflicting in nature. Minimizing some of them will yield a straighter alignment; whereas, minimizing others would make the alignment circuitous. Therefore, the goal of the multiobjective optimization approach is to handle the trade‐off amongst the highway alignment design objectives and present a set of near optimal solutions. The highway alignment objectives, i.e., cost functions, are not continuous in nature. Hence, a special genetic algorithm based multi‐objective optimization algorithm is suggested The proposed methodology is demonstrated via a case study at the end. 相似文献
175.
针对船舶六自由度转台电液伺服系统的参数整定问题,提出一种基于多目标遗传算法和多属性决策的PID参数设计方法,综合考虑了系统超调量、稳定时间和ITAE指标,采用多目标遗传算法求出Pareto最优解。使用客观赋权的信息熵法对最优解的属性进行权值计算,然后采用逼近理想解的排序方法(TOP—SIS)进行多属性决策(MADM)研究。计算了转台电液伺服控制的数值算例,结果表明本文提出的联合方法通用性好,所设计的PID性能优异,适合工程实际应用。 相似文献
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正交异性组合桥面由于其较好的抗疲劳性能和静力承载能力、相对较轻的自重近年来在实际工程中得到较多应用。正交异性组合桥面通常由正交异性钢板和混凝土层组成,在加入混凝土层后结构刚度发生较大变化,若正交异性板仍采用传统正交异性钢桥面的构造形式将会造成不必要的钢材用量和焊接量增加。采用遗传算法,以单位面积造价最小为目标,结合现有规范考虑了构造约束和承载能力约束两类约束条件,采用两种应力控制方案,对不同桥面板跨度和混凝土厚度的正交异性组合桥面的构造进行优化。同时解决了构造改变导致荷载分配改变对承载能力分析造成的影响。优化结果表明,桥面跨度4.5m时,与未优化组合桥面相比,优化方案用钢量可降低1.7%~10.1%,焊接量可降低16.5%~31.8%。 相似文献
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179.
四连杆式独立悬架运动学分析与优化 总被引:1,自引:0,他引:1
四连杆式悬架是技术比较先进的悬架形式。可以从设计上保证车辆良好的直线行驶性能并最大程度减轻载荷的影响。建立了四连杆式悬架多刚体系统模型并对车轮定位参数等特性进行仿真,运用多目标函数的最优化方法对悬架的结构参数进行优化。并将优化前后的车轮定位参数运动学特性进行对比,说明进行悬架结构参数的优化对于提高悬架性能的重要作用。 相似文献
180.
停车换乘选址问题是城市交通网络设计研究的重点领域,已有研究的优化目标多集中在系统总费用方面,而对交通可持续发展方面考虑不足。为此,提出综合考虑多方面目标的停车换乘设施选址优化模型及其求解算法。首先,基于超网络理论,提出多方式城市交通系统的超网络模型并定义O-D (Origin-destination)间的超路径、有效超路径及子路径,结合出行者出行过程及交通网络拥挤特征,给出超路径费用的数学表达;其次,基于多方式交通网络随机均衡配流结果,构建交通总阻抗、污染物排放量以及交通系统公平性等系统优化指标的计算模型,并建立用以描述停车换乘设施选址问题的多目标优化模型;进而,以多目标系统优化模型为上层问题,以超网络下满足Logit分配的多方式交通网络配流模型为下层问题,构建描述城市多方式交通系统停车换乘设施选址问题的双层规划模型,并基于模型特征,结合“记录-搜索”思想设计非支配排序遗传算法进行求解;最后,基于Sioux Falls网络设计算例。研究结果表明:算法能够在有限的步骤内搜索到90%以上的Pareto最优解;平均而言,停车换乘措施使得交通总阻抗减小了0.31%,污染物排放量减少了7.32%... 相似文献