基于网络化训练的通用教练机机队配置优化模型

为了优化网络化飞行训练下通用教练机(初级、中级、高级)机队配置以降低机队训练成本,将网络化训练下多训练基地、多执照阶段的航空驾驶员培训过程抽象为一个带权有向网络图,通过综合考虑航空驾驶学员总人数限制和流动平衡条件,教练机机队可用飞行时间限制,以及各类通用教练机在训练基地的最少投放飞机数限制等因素,构建以通用教练机机队训练成本最小化为目标函数的机队配置优化数学模型。针对"3个训练基地,一个训练周期培养1 000名航线驾驶员"的案例,仿真结果表明,与飞行航校现有普遍的训练模式相比,该模型能够在培训同等航空驾驶学员数量基础上将3个训练基地所配置的通用教练机机型数量分别降至2种、1种和2种,且将机队训练总成本降低2.7%。研究结果表明,网络化训练模式能够减少训练基地配置的教练机机型数量,并显著降低机队训练总成本。     

机场容量限制下的多重分派枢纽航线网络设计

为了探索枢纽航线网络的设计,提出了机场容量限制下的多重分派枢纽航线网络的设计方法。以航空客运O-D流为基础,将枢纽选择和航线设计两个阶段综合考虑,用机场吞吐量衡量机场容量限制,建立多商品网络流模型,量化成本折扣因子、枢纽数目对枢纽航线网络总成本的影响程度。中国航空客运吞吐量排名前20的城市组成算例,用IBM ILOG CPLEX12.2计算出设计方案的时间不超过14.87 s。算例证明,机场容量限制会增加枢纽航线网络的总成本,但O-D流分布过度密集的现象减轻,抗拥堵性增强。枢纽间成本折扣因子的减小和枢纽数目的适当增加都能够降低枢纽航线网络的总成本。最后,绘制枢纽航线网络结构图,为枢纽航线网络的设计提供指导。     

考虑内陆转运的集装箱班轮运输网络设计方法

为了优化班轮公司航线网络,降低运营成本,针对始发地或目的地位于内陆,且内陆与港口间存在转运OD流的班轮航线进行网络设计。基于Logit和整数线性规划等方法,将内陆OD流转化为港到港需求,建立集装箱班轮航运网络评估模型。模型以总成本最小为目标,同时满足货运需求、装卸港转运时间以及合理安排运力等约束,利用IOLG CPLEX优化软件进行求解。将模型用于某班轮公司航线网络设计,与现有结构相比优化结果显示：在保持总运量大致持平的基础上,可将原有船队规模从81条航线、289只船舶有效缩减到77条航线和269只船舶。表明该模型能够有效降低班轮航线运营成本,具有较大的实践意义。     

面向快递同城运输的车辆路径问题研究

为降低运输成本,研究了快递同城运输中的车辆路径问题。建立多车型,含时间窗约束、容量约束、车辆限行约束,并考虑错峰交货的,以最小化运输成本为目标的混合整数规划模型。提出以点到点集的距离之和作为邻域搜索优先指标的构造性启发式算法,设计了基于“路径−车型对”的列生成算法,初始列由启发式算法求得。实验结果显示,对于120个点的大规模问题,列生成算法只需175秒就能得到近似最优解,验证了该算法的有效性及对一定规模内快递同城运输问题的适用性。     

考虑动态需求的生鲜商品物流配送优化方法研究

目的 针对生鲜商品配送过程中客户需求的变化,协调静态与动态客户需求之间的关系,合理规划路径,并降低物流总成本。方法 首先考虑客户生鲜需求的多样化温控区间、随机订单请求时间及动态需求量等因素,构建物流总成本最小化的整数规划模型。然后,设计基于高斯混合聚类的改进蚁群算法求解该模型,并提出动态需求处理策略,用于路径的再优化。其次,通过与粒子群算法、遗传算法和鲸鱼优化算法进行对比分析,验证文中设计算法的有效性。最后,以重庆市某生鲜配送网络为例,对比分析优化前后的运营指标,并探讨生鲜商品价值损失水平与物流总成本之间的关系。结果 经优化后,物流总成本下降了22.35%,其中惩罚成本、价值损失、配送成本和温控成本分别下降了39.84%、61.84%、29.80%、57.00%。结论 文中所提的模型、算法和动态需求处理策略可以合理规划配送路径,有效降低了总成本,为考虑动态需求的生鲜配送网络优化提供了参考。     

混合轴辐式城乡一体化物流网络构建研究

为了降低城乡物流成本和提高城乡物流效率,以成本为导向构建了一种同时满足农产品与非农产品物流需要,并允许直达运输的混合轴辐式城乡一体化物流网络规划模型,设计了求解该模型的禁忌搜索算法。为了验证模型及算法的有效性,进行了包含6个节点的网络仿真分析和针对运输折扣系数α、β,货损系数θ₁、θ₂的灵敏度分析。仿真结果表明,选择节点4和节点6作为枢纽节点,节点2与节点3建立直达运输时,网络最优总成本为538 114;α、β分别从0增加到1,θ₁、θ₂分别从0增加到0.5,对应的网络总成本分别增加了4.1%、3.7%、4.2%、0.8%。构建的混合轴辐式城乡一体化物流网络能有效降低物流成本,提高效率,可为实际应用提供参考。     

基于BP神经网络的真空度测量精度改善方法研究

针对真空度测量精度低的现状,提出一种真空度测量精度改善方法。以热偶规为研究对象,基于BP神经网络设计真空度测量系统。通过设计BP网络结构,采用三种不同的算法对网络权值进行训练,以获得尽可能稳定、精度更高的BP神经网络。对三种算法由测试样本进行测试,三种算法训练的网络能较大程度地提高真空度测量精度,受热丝电流、热丝冷阻干扰影响大大减小;而且最速下降法对应的网络输出值波动较大,附加动量法次之,自适应学习速率调整法对应的输出值波动最小,波动量小于0.01。     

基于时间窗和多仓温控的生鲜商品配送车辆路径优化问题

目的 针对当前生鲜商品配送效率低和成本高等问题,采用车仓温度可控的多仓车辆作为配送装备,并结合时间窗等约束,研究基于时间窗和多仓温控的生鲜商品配送车辆路径优化问题。方法 建立最小化物流运营成本和车辆使用数量的双目标模型,然后设计基于Clarke-Wright节约算法的非支配排序遗传算法（CW-NSGA-Ⅱ）求解该模型。利用CW节约算法生成初始配送路径,以提高初始解的质量,并设计精英迭代策略,以提高算法的寻优性能。结果 基于改进的Solomon算例,将文中所提算法与多目标粒子群算法、多目标蚁群算法、多目标遗传算法进行了对比,验证了CW-NSGA-Ⅱ算法的求解性能。结合实例,对多仓车辆使用数量、温控成本和运营成本等指标进行对比分析,结果表明,经优化后多仓车辆使用数量减少了35.7%,温控成本减少了39.2%,物流运营总成本减少了47.7%。结论 文中所提模型和算法能够有效优化配送路径,降低运营成本,为构建高效率、低成本的生鲜配送网络提供了理论支持和决策参考。     

自行火炮驾驶员多种工作负荷建模与评价研究

本文旨在获得一种自行火炮驾驶员多种工作负荷综合评价方法。针对驾驶员高作业负荷、高认知负载、热负荷、心理应激等情况,运用工效学原理和主观负荷评价技术法构建影响驾驶员工作负荷的指标体系,基于网络分析法建立复杂电磁环境下驾驶员多种工作负荷评价模型,以JD1825和JD2532型号底盘为例进行验证。结果表明,本评价方法能有效评价驾驶员多种工作负荷各种因素之间的关联影响,可为自行火炮驾驶舱改进设计、优化驾驶舱资源配置提供参考依据。     

基于时空网络模型的灭火救援路径优化方法

为火灾救援现场配置合理的灭火救援路径,是最大限度提高救援效率、提升救援效果的关键。该文以灭火救援路径优化方法为核心研究内容,首先从救援时间和救援距离2个约束出发,构建灭火救援路径的时空网络模型。针对时空网络模型进一步提出基于遗传算法的灭火救援路径优化方案,在给出具体的求解流程以后给出了一个实例用来求解遗传算法求解过程中的编码设计、初始种群生成、对应灭火救援实际问题。灭火救援路径优化测试试验证明了该文构建的时空网络模型和遗传算法路径优化方法的有效性。     

Integrating fleet replacement and pilot training schedules for airborne service helicopters

In this study, we examine an integrated problem involving fleet replacement and pilot training scheduling for airborne service helicopters. Two objectives, minimizing the total cost and the number of batches of pilot training, are considered based on the practical requirements. Multi-objective programming combined with a time–space network technique is applied to solve the problem. Numerical tests, in reference to the operations of a Taiwanese organization, are carried out to demonstrate the performance of the proposed model. A comparison of the proposed model and two single-objective models corresponding to the two objectives is also presented.     

可靠的不完全轴辐网络设计模型

不完全轴辐网络的枢纽被毁坏将导致网络运输成本大量增加，研究可靠的不完全轴辐网络设计模型有利于减少枢纽毁坏带来的不利影响。在不完全轴辐网络设计模型基础上，针对枢纽毁坏后需求分配的两种模式 (single backup/multiple backup，SB/MB) ，构建可靠的不完全轴辐网络设计问题 (reliable incomplete hub-and-spoke network design problem，RIHNDP) 模型并线性化，通过算例验证了模型的有效性。结果表明，需求最多的节点总被选为枢纽。不同模式下的后补枢纽、分配方案可能不同：从管理者角度，为了降低管理难度，可采用SB模式；从出行者角度，为了更低的运输成本，宜采用MB模式。因为正常情况下可靠的不完全网络运输成本比不考虑枢纽毁坏的不完全网络高 (不超过5%，网络越密相差越小) ，有必要考虑枢纽毁坏设计可靠的网络，但当枢纽毁坏发生后RIHNDP能避免枢纽毁坏后网络不连通的情况，其运输成本比不考虑枢纽毁坏的不完全网络低。     

Reliability of a computer network in case capacity weight varying with arcs, nodes and types of commodity

The computer network can be modeled as a capacitated-flow network. This paper concentrates on a two-commodity capacitated-flow network with three characters: (1) nodes as well as arcs have multiple possible capacities and may fail, (2) each component (arc/node) has both capacity and cost attributes; and (3) the capacity weight varies with arcs, nodes and types of commodity (or named file). We study the possibility that a given quantity of two types of files can be transmitted through this network simultaneously under the budget constraint. Such a possibility is named the system reliability which is a performance index to measure the quality level of supply demand systems such as computer, telecommunication, electric-power transmission and transportation systems. The approach of minimal paths is applied to describe the relationship among flow assignments and capacity vectors. A simple algorithm in terms of minimal paths is proposed to evaluate the system reliability.     

Harmony search optimization algorithm for a novel transportation problem in a consolidation network

This article presents a new harmony search optimization algorithm to solve a novel integer programming model developed for a consolidation network. In this network, a set of vehicles is used to transport goods from suppliers to their corresponding customers via two transportation systems: direct shipment and milk run logistics. The objective of this problem is to minimize the total shipping cost in the network, so it tries to reduce the number of required vehicles using an efficient vehicle routing strategy in the solution approach. Solving several numerical examples confirms that the proposed solution approach based on the harmony search algorithm performs much better than CPLEX in reducing both the shipping cost in the network and computational time requirement, especially for realistic size problem instances.     

A probabilistic computational framework for bridge network optimal maintenance scheduling

This paper presents a probabilistic computational framework for the Pareto optimization of the preventive maintenance applications to bridges of a highway transportation network. The bridge characteristics are represented by their uncertain reliability index profiles. The in/out of service states of the bridges are simulated taking into account their correlation structure. Multi-objective Genetic Algorithms have been chosen as numerical tool for the solution of the optimization problem. The design variables of the optimization are the preventive maintenance schedules of all the bridges of the network. The two conflicting objectives are the minimization of the total present maintenance cost and the maximization of the network performance indicator. The final result is the Pareto front of optimal solutions among which the managers should chose, depending on engineering and economical factors. A numerical example illustrates the application of the proposed approach.     

Integrated decision support framework for distribution network design

In the current business environment of competition shifting from company-to-company to supply chain against supply chain, there is an increasing need for logistics providers (LSP) to gain cost effectiveness with no compromise on service levels. One key initiative that LSP can undertake is to allocate and utilise their storage and transportation assets optimally. The current work is an attempt in that direction and provides a hands-on decision support framework that integrates MCDM, network optimisation, and discrete event simulation to address distribution network design and transport optimisation. The use case of PT Pos Indonesia in the metropolitan area of Greater Surabaya highlights the benefits of combining ICT tools with well-established best practices in supply chain management. Findings of this work highlight that the number of distribution facilities for the case at hand should be reduced from nine to four. Compared to the existing, the identified network configuration unlocks potential cost saving in transportation and warehousing of 18%–22%, reduces CO₂ emissions by nearly 30%, with no deterioration in service level. Managerial implications about transportation policies are highlighted in the conclusive part of this paper.     

A multi-objective optimization model for hub network design under uncertainty: An inexact rough-interval fuzzy approach

This article proposes a multi-objective mixed-integer model to optimize the location of hubs within a hub network design problem under uncertainty. The considered objectives include minimizing the maximum accumulated travel time, minimizing the total costs including transportation, fuel consumption and greenhouse emissions costs, and finally maximizing the minimum service reliability. In the proposed model, it is assumed that for connecting two nodes, there are several types of arc in which their capacity, transportation mode, travel time, and transportation and construction costs are different. Moreover, in this model, determining the capacity of the hubs is part of the decision-making procedure and balancing requirements are imposed on the network. To solve the model, a hybrid solution approach is utilized based on inexact programming, interval-valued fuzzy programming and rough interval programming. Furthermore, a hybrid multi-objective metaheuristic algorithm, namely multi-objective invasive weed optimization (MOIWO), is developed for the given problem. Finally, various computational experiments are carried out to assess the proposed model and solution approaches.     

Hazardous materials transportation: a risk-analysis-based routing methodology

This paper introduces a new methodology based on risk analysis for the selection of the best route for the transport of a hazardous substance. In order to perform this optimisation, the network is considered as a graph composed by nodes and arcs; each arc is assigned a cost per unit vehicle travelling on it and a vehicle capacity. After short discussion about risk measures suitable for linear risk sources, the arc capacities are introduced by comparison between the societal and individual risk measures of each arc with hazardous materials transportation risk criteria; then arc costs are defined in order to take into account both transportation out-of-pocket expenses and risk-related costs. The optimisation problem can thus be formulated as a 'minimum cost flow problem', which consists of determining for a specific hazardous substance the cheapest flow distribution, honouring the arc capacities, from the origin nodes to the destination nodes. The main features of the optimisation procedure, implemented on the computer code OPTIPATH, are presented. Test results about shipments of ammonia are discussed and finally further research developments are proposed.     

一种结合网络编码的路径代价衡量方法

针对无线路由协议中的路径代价衡量问题,结合网络编码改善无线节点信息互换的思想,提出了一种结合网络编码的路径代价衡量方法--RMNC,其核心思想是利用流量参数反映信息流的网络编码"搭乘"程度和逐节点计算路径的代价.通过将传输流流量参数和路径中节点左右链路信息流流量参数进行运算,获得路径上的各个节点的传输代价;网络中某一条路径的代价等于组成这条路径的节点传输代价之和,通过比较不同路径的逐节点计算代价值,获得最短路径.分析和模拟测试结果表明,RMNC可以有效地获得结合网络编码的最短路径,达到提高传输性能的目的.尽管传输延时有所增加,但可以接受,方法可行.