Solving the station-based one-way carsharing network planning problem with relocations and non-linear demand

One-way station-based carsharing systems allow users to return a rented car to any designated station, which could be different from the origin station. Existing research has been mainly focused on the vehicle relocation problem to deal with the travel demand fluctuation over time and demand imbalance in space. However, the strategic planning of the stations’ location and their capacity for one-way carsharing systems has not been well studied yet, especially when considering vehicle relocations simultaneously. This paper presents a Mixed-integer Non-linear Programming (MINLP) model to solve the carsharing station location and capacity problem with vehicle relocations. This entails considering several important components which are for the first time integrated in the same model. Firstly, relocation operations and corresponding relocation costs are taken into consideration to address the imbalance between trip requests and vehicle availability. Secondly, the flexible travel demand at various time steps is taken as the input to the model avoiding deterministic requests. Thirdly, a logit model is constructed to represent the non-linear demand rate by using the ratio of carsharing utility and private car utility. To solve the MINLP model, a customized gradient algorithm is proposed. The application to the SIP network in Suzhou, China, demonstrates that the algorithm can solve a real world large scale problem in reasonable time. The results identify the pricing and parking space rental costs as the key factors influencing the profitability of carsharing operators. Also, the carsharing station location and fleet size impact the vehicle relocation and carsharing patronage.     

Optimal recharging strategies for electric vehicle fleets with duration constraints

Electrical vehicles (EVs) have become a popular green transportation means recently because they have lower energy consumption costs and produce less pollution. The success of EVs relies on technologies to extend their driving range, which can be achieved by the good deployment of EV recharging stations. This paper considers a special EV network composed of fixed routes for an EV fleet, where each EV moves along its own cyclic tour of depots. By setting up a recharging station on a depot, an EV can recharge its battery for no longer than a pre-specified duration constraint. We seek an optimal deployment of recharging stations and an optimal recharging schedule for each EV such that all EVs can continue their tours in the planning horizon with minimum total costs. To solve this difficult location problem, we first propose a mixed integer program (MIP) formulation and then derive four new valid inequalities to shorten the solution time. Eight MIP models, which were created by adding different combinations of the four valid inequalities to the basic model, have been implemented to test their individual effectiveness and synergy over twelve randomly generated EV networks. Valuable managerial insights into the usage of valid inequalities and the relations between the battery capacity and the total costs, number of recharging facilities to be installed, and running time are analyzed.     

A probabilistic optimization model for allocating freeway sensors

This paper proposes a sensor location model to identify a sensor configuration that minimizes overall freeway performance monitoring errors while considering the consequences of probabilistic sensor failures. To date, existing sensor location models for freeway monitoring inherently assume that either deployed sensors never fail or the consequences of sensor failure are trivial matters. However, history has revealed that neither assumption is realistic, suggesting that ignoring failures in sensor allocation models may actually produce a significantly suboptimal configuration in the real world. Our work addresses this dilemma by developing a probabilistic optimization model that will minimize the error expectation by examining all possible failure scenarios, each with an occurrence probability. To ensure the scenario completeness and uniqueness, a sensor failure scenario is represented by using a binary string with 1 indicating an operational sensor at a given site and 0 for sensor failure or no sensor deployed. When applied to a case study network, it is shown that an optimal configuration that considers sensor failure is significantly different from an optimal configuration that ignores sensor failure, revealing that sensor failures pose non-trivial consequences on performance monitoring accuracy.     

The design of electric vehicle charging network

The promotion of Electric Vehicles (EVs) has become a key measure of the governments in their attempt to reduce greenhouse gas emissions. However, range anxiety is a big barrier for drivers to choose EVs over traditional vehicles. Installing more charging stations in appropriate locations can relieve EV drivers’ range anxiety. To determine the locations of public charging stations, we propose two optimization models for two different charging modes - fast and slow charging, which aim at minimizing the total cost while satisfying certain coverage goal. Instead of using discrete points, we use geometric objects to represent charging demands. Importantly, to resolve the partial coverage problem (PCP) for networks, we extend the polygon overlay method to split the demands on the road network. After applying the models to Greater Toronto and Hamilton Area (GTHA) and to Downtown Toronto, we show that the proposed models are practical and effective in determining the locations of charging stations. Moreover, they can eliminate PCP and provide much more accurate results than the complementary partial coverage method (CP).     

A toll-based bi-level programming approach to managing hazardous materials shipments over an intermodal transportation network

This research proposes a bi-level bi-objective model to regulate the usage of rail intermodal terminals for hazardous materials (hazmat) shipments, where government imposes tolls to deter carriers from using certain terminals. The complexity of the resulting mathematical program motivates the development of a hybrid speed-constrained multi-objective particle swarm optimization algorithm, which is then integrated with CPLEX, to solve the model. Through a real problem instance based on the intermodal service chain of Norfolk Southern in US, the toll-setting model is examined and further compared with a regular network design approach, in which certain terminals are closed to hazmat containers. The computational results show that the toll-setting policy is more practical and efficient, and the two models can be combined as a two-stage strategy in long-term hazmat transportation regulations. Additional managerial insights are derived for different stakeholders.     

Applying spatial-temporal analysis and retail location theory to public bikes site selection in Taipei

In order to turn Taipei into a sustainable, green metropolis, in 2009, the Department of Transportation of Taipei City Government launched a public bike rental system (YouBike) to meet people’s daily commute and/or leisure needs. Given that users may return bikes to sites differing from their starting locations, rental stations frequently lack bikes or bike racks. This study sought to identify lacking-bike and/or lacking-bike rack hot spots utilizing spatial-temporal analysis. In addition, it applied retail location theory to determine site selection of further rental stations. Historical data indicated that shortage of bikes was much more severe than shortage of bike racks in the YouBike public bike system and lacking-bike and lacking-bike rack hot spots were clustered significantly. The study demonstrated that spatial-temporal analysis can be used to effectively identify rental stations’ spatial patterns, determine the most suitable locations for further installation of rental stations, help to provide public bike users with a more effective rental system, and greatly assist public bikes’ operational management and decision-making in Taiwan.     

散货船关键节点结构建造的监控方法及优化

造船精度的提高对散货船关键节点的结构监控提出了更高的要求,对关键节点结构监控使用的模板和检验线的方法引入理论间隙和容许误差的数学概念,综合考虑现场监控的可行性,提出优化方法,可提高监控的精度和效率,为船厂对关键节点的自我监控和现场检验提供参考。     

静水中并行两船水动力干扰数值研究

为比较分析单船与两船并行航行的水动力差异,探讨静水中两船并行时漂角、船船相对位置对船体阻力、侧向力及摇首力矩的影响规律,文章基于RANS方程采用SST k-棕湍流模型,数值分析了某两船静水并行时船船相互作用。研究表明：不同漂角下两船中对中并行时,船体所受阻力均较单船航行时有所增大且受到指向两船中间的附加侧向力;当两船并行斜航的漂角相反时,同一船舶位于迎流侧较背流侧时船体受力存在一定差异;两船并行直航时,船船相对位置对船体受力有较大的影响,当两船纵向间距小于一倍船长时,船船相互作用较为显著,在不同横向间距下,船体受力随纵向间距的变化规律相同,在一定纵向间距下,船间横向间距越小船船相互作用越强。     

变化趴杆角度对起重船吃水影响的计算

本文对固定趴杆式起重船在固定吊重下，变化趴杆角度对起重船吃水的影响进行了分析，并结合工程实例进行验证计算，为其他海上吊装作业提供参考及借鉴。     

龙门吊旧机改造中测速编码器几种传动方式的选用

为了提高效率,在对龙门吊旧机进行的改造时,加装了测速编码器.介绍了3种测速编码器的传动方式以及它的各自的利弊.选择了一种最佳方案取得了很好效果.可供参考.