基于车种代用的铁路网空重车调配优化研究

为促进空重车协同高效调配并提高货主满意度，在铁路空车调配经典模型的基础上，提出一种考虑车种代用的空重车协同调配模型，该模型考虑站点空车需求供给的随机分布、货车保有量、货运计划、空车车流直达等约束，以重车收入、车种代用费用、货运需求损失费用、空车调配费用的总收益最大化为目标，使得模型更加接近生产实际。针对构建的调配模型设计改进的蚁群算法，该算法采用信息素的局部更新以及全局更新来指导蚂蚁的状态转移。以某铁路网为例，研究结果中实现车种代用的敞车共有1 566车，在调配重车数中占比61.40%，可见合理的车种代用可以更大程度地满足运输需求；当敞车、平车单位空走费用不变，降低棚车单位空走费用时，对提高铁路运输收益更有效果。     

基于路网的多车种空车调配优化方案研究

在分析现有典型空车调配模型特点的基础上,基于路网结构,核心考虑区间通过能力和不同车种间代用因素,将空车调配相关的走行费用、车种代用费用,以及库存费用共同纳入目标体系,构建了多车种空车调配改进模型,使空车调配更加符合铁路运输实际.通过算例模拟分析,验证了模型的可行性.     

基于应急物资优先权的铁路空车调配研究

近年来突发性的自然灾害发生频繁,应急物资调运优化问题成为研究热点.基于模糊综合评判方法对应急物资优先权进行了分析,并结合车种代用,构建了考虑应急物资优先权的车种代用空车调配模型.分析表明,若适当选取多目标的权重系数,则该多目标模型既适用于应急救援过程中的物资调运,又适用于日常的物资调运.     

基于遗传模拟退火算法的战时物流配送路径优化研究

综合考虑战时物流配送车辆路径问题（VRP）的多目标评价，提出多属性道路网络下战时物流配送的VRP算法，并建立完全分层优化模型。将进化算法与传统优化技术相结合，构造了模型的两层求解算法，第一层采用遗传算法和模拟退火算法混合的GASA算法，第二层采用枚举法。并以成品燃油配送为例进行了实验，结果表明算法较标准遗传算法更有效。     

基于遗传算法的城际客运专线列车开行方案研究

分析城际客运专线列车开行方案的特点。以旅客时间消耗最小为目标，建立城际客运专线旅客列车开行方案的最小费用流模型。根据模型的特点，设计相应的遗传算法，并对遗传算法的适应值函数、算法步骤和算法复杂度进行分析。分析结果表明，该算法是一个收敛于全局最优解的近似有效算法。     

一种相互淘汰的物流中心选址方法

在建立评价指标体系的基础上,对费用指标通过成本模型的遗传算法求解,得出费用最佳备选中心;然后利用模糊综合评判对评价指标层中的其他指标评价排序,用定性的方法选出最佳备选中心。最后对两组方案进行相互淘汰,得出最终解。     

压缩天然气：汽车重要代用能源

进入本世纪以来，我国石油对外依存受逐年递增，2011年已达56．5％，国内汽车排放标准的几次升级，寻求经济性和环保性都好的汽车代用燃料成了业界普遍关心的一个问题，压缩天然气（CNG），液化天然气（LNG）、液化石油气（LPG）、甲醇汽油、乙醇汽油、生物柴油二甲醚．煤层气、沼气等燃料都成了可供选择的代用燃料，应当认真调研和决策。     

物流配送中心优化选址问题研究

基于物流配送中心成本分析,建立物流配送中心优化选址模型。配送中心优化选址模型属“0-1”混合非线性规划问题,具有NP难性质。运用遗传算法,对配送中心优化选址模型进行仿真求解。最后通过一个实例验证了该选址模型的科学性和遗传算法求解该模型的有效性。     

铁路省际煤炭调运的格局及优化

铁路煤炭运输在煤炭运输中占主导地位,影响着煤炭的供需平衡。在对我国铁路省际煤炭调运格局进行分析的基础上,构建了铁路省际煤炭调运的优化模型,并进行优化分析。研究表明:2001—2010年我国铁路煤炭运输量增长率低于煤炭生产增长率,铁路运输在各省煤炭调运中发挥着不同的作用;优化后的铁路省际煤炭调运成本比优化前节约了82.2亿元,平均运输距离缩短了98.3 km,各供给地和需求地的铁路煤炭流向和流量进行了重新分配。     

基于随机机会约束的空车调整模型的研究

通过对比空车调整问题的确定性模型与实际问题之间的差异，提出一类随机机会约束模型来模拟实际空车调整问题。通过引入概率模拟实际问题中的不确定因素，将确定性模型转化为不确定性模型，以使模型能更准确的反映实际，并将经济学指标作为评价标准。通过遗传算法求解算例，表明模型和方法的有效性。     

Integrating berth allocation and quay crane assignments

In this study, a dynamic allocation model using objective programming for berth allocation and quay crane assignments was preliminarily developed based on rolling-horizon approach. Afterwards, a hybrid parallel genetic algorithm (HPGA), which combined parallel genetic algorithm (PGA) and heuristic algorithm, was employed to resolve the proposed model. Furthermore, a simulation was conducted to evaluate the HPGA and to execute relevant gene repair techniques. Eventually, the numerical experiments on a specific container terminal were applied to illustrate the proposed models and algorithms. In so doing, the effectiveness of the proposed approach was verified.     

Accounting for population exposure to vehicle-generated pollutants and environmental equity in the toll design problem

The emissions generated by motor vehicles remain a major source of air pollutants that affect public health and contribute to anthropogenic climate change. These negative externalities can be reduced, in part, with the implementation of environmentally oriented road pricing schemes, which can be designed using optimization-based approaches. In this paper, a toll design problem is proposed for determining toll locations and levels that minimize the expected human exposure to air pollutants and the related environmental inequalities, subject to constraints on pollutant concentration levels and implementation costs. The practical use of the proposed problem is hindered in most real-world applications by the computational costs associated with the evaluation of candidate solutions, as is common for network design problems. Furthermore, the problem cannot be expressed analytically given the multiple types of models (e.g., traffic assignment, emissions, air dispersion models) that would be required to evaluate a single design alternative. For these reasons, a derivative-free surrogate-based solution algorithm is proposed for mixed integer problems like the ones considered here. Numerical examples are used to illustrate possible applications of the proposed model and to test the performance of the surrogate-based algorithm. Relative to a joint simulated annealing-genetic algorithm heuristic and a genetic algorithm-based approach, the proposed algorithm found better solutions in fewer function evaluations.     

A robust optimization approach to the integrated berth allocation and quay crane assignment problem

This paper investigates the integrated berth allocation and quay crane assignment problem in container terminals. A deterministic model is formulated by considering the setup time of quay cranes. However, data uncertainties widely exist, and it may cause the deterministic solution to be infeasible. To handle the uncertainties, a robust optimization model is established. Furthermore, to control the level of conservativeness, another robust optimization model with the price constraints is proposed. A genetic algorithm and an insertion heuristic algorithm are suggested to obtain near optimal solutions. Computational experiments indicate that the presented models and algorithms are effective to solve the problems.     

Integration of inventory and transportation decisions in a logistics system

This paper addresses some of the challenges faced by a company which is responsible for delivering coal to its four subsidiaries situated along a river, through river hired or self-owned vessels. We propose to adopt a vendor managed inventory concept that involves establishment of a central warehouse at the port, and apply the Markov Decision Process (MDP) to formulate both ordering and delivery problems, considering different transportation modes, costs, and inventory issues. An efficient algorithm is developed for solving the MDP models. Our computational tests show that the proposed strategy can significantly reduce the overall system costs while maintaining smooth Just-in-Time supplies of coal to the subsidiaries.     

The optimization model for the location of maritime emergency supplies reserve bases and the configuration of salvage vessels

This paper studies the location–allocation–configuration problem of emergency resources in a maritime emergency system and it proposes a discrete nonlinear integer-programming model, which integrates the location, allocation and the configuration problem. The model is converted into a two-stage model keeping the calculation logic. It designs a hybrid heuristic algorithm and a genetic algorithm. The test results show that the hybrid heuristic algorithm is more efficient than the genetic algorithm, the sensitivity analysis studies the influence of some parameters to the final solution and the Uncertainty–Sensitivity justification tool is used to evaluate the assumptions.     

双线铁路通过能力图解计算方法研究

为了准确计算双线铁路通过能力,提出一种双线铁路线路通过能力图解计算的新思路,借鉴作业车间调度问题的建模方法,构建列车运行图优化编制的析取图模型,设计遗传算法求解,实现以时间跨度最小为目标的双线铁路运行图优化编制,以支撑双线铁路线路通过能力的图解计算。通过算例测试验证了运行图优化编制方法,利用该方法计算单类列车的开行数量,对多类列车混合开行情况下的扣除系数进行分析,运用帕累托最优原理描述多种类列车开行情况下的线路通过能力。     

Capacity-oriented passenger flow control under uncertain demand: Algorithm development and real-world case study

This paper proposes a problem of passenger flow organization in subway stations under uncertain demand. The existing concepts of station service capacity are extended and further classified into three in different demand scenarios. Mathematical models are put forward to measure the three capacities and a unified simulation-based algorithm is developed to solve them. To increase computing speed, data envelopment analysis (DEA) and genetic algorithms (GA) are embedded in this algorithm. A case study will demonstrate the performance of the proposed algorithm and give a detailed procedure of passenger flow control based on station service capacity in various demand scenarios.     

Liner hub-and-spoke shipping network design

This paper proposes a liner hub-and-spoke shipping network design problem by introducing the concept of a main port, as well as some container shipping constraints such as multi-type container shipment and transit time constraints, which are seldom considered in the previous studies. It develops a mixed-integer programming model with nonconvex multi-linear terms for the proposed problem. An efficient genetic algorithm embedded with a multi-stage decomposition approach is developed to solve the model. Numerical experiments are carried out to assess the effectiveness of the proposed model and the efficiency of the proposed algorithm.     

Optimization of loading sequence and rehandling strategy for multi-quay crane operations in container terminals

In this paper, we consider the optimization of loading sequence and rehandling strategy in the terminal operation. We present an optimization strategy to minimize the number of rehandles, and establish a mathematical model to integrate the loading sequence and the rehandling strategy under the parallel operation of multi-quay cranes. Furthermore, we give an improved genetic algorithm to solve the model. We show the efficiency of the optimization strategy and algorithm by comparing them with previous strategies and heuristics.     

基于遗传算法的应急系统选址优化

对社会各种突发事件进行处理的应急系统中,应急服务设施的选址涉及经济、技术、社会、安全等多方面因素。考虑到这一选址问题的特殊性,提出一种求解的自适应遗传算法。为此提出应急系统选址的多目标决策模型,按照自适性遗传算法的设计步骤,通过实例计算,确定应急系统选址的最佳组合方案。