改进的遗传算法在战时油料运输车辆路径问题中的应用研究

文章首先对战时油料运输车辆路径问题（VRP）进行了分析,阐述了战时油料运输车辆路径问题的优化目标,并建立了多目标的优化模型;接着简介了遗传算法的优缺点,并设计了一种改进的遗传算法运用到问题的求解中;最后举例进行了计算和分析．验证了模型和算法的有效性     

运输问题中一种有效降低初始目标函数值的方法

本文对运输问题中的最小元素法进行了改进，寻找到一种在寻找运输问题最优解时能有效降低初始方案的目标函数值．以减少求解过程中迭代次教的方法。     

分层物流网络设计及启发式算法求解研究

按照服务小区将物流设施分层划分,在传统物流网络的基础上设计了分层网络.以建设费用最小、运输费用最小为目标,建立了多目标整数规划模型.模型分解为选址问题和运输问题,并采用邻域搜索算法计算选址问题、免疫克隆算法求解运输问题,设计了求解模型的启发式算法.算例说明了算法的可行性和有效性.最后,在给定不同建设、运输费用权重参数的条件下对零售商的建设数鼍进行了灵敏度分析.     

基于遗传算法的多目标集装箱多式联运运输优化模型

基于集装箱多式联运在进行门到门的运输过程中可以选择多种运输方式和路径的组合进行优化运输这个特点，本文将多式联运的运输优化问题转化成为一个最短路径问题，以成本和时间为优化目标建立了选择最优路径的模型，并选择遗传算法作为求解算法对实例问题进行了求解验证。     

基于多目标的双层集装箱配载研究

从物流运输效率和运输安全的角度，研究提出入选配载方案的箱数最大（“甩箱”摄少），车辆的平均重心高最低和车轴平均集重差最小为目标，基干双层集装箱的双层装载结构的运输安全条件为约束的配载方案优化的多目标模型，设计了求解该问题的距离理想点算法，对多目标函数极值进行加权整合得到最优配载方案，并通过实例验证了模型的有效性。     

基于匈牙利算法的运输问题改进算法

基于运输问题的模型和特点,提出了一种与匈牙利算法结合的改进算法,匈牙利算法作为一种较成熟的基本算法,在计算运输问题时省去大量求解检验数的计算。改进算法将运输问题分解成多个指派问题,利用匈牙利算法求解分解后的指派问题,最后将所有指派问题的结果求和得到最优解。给出了一个改进算法的案例,详细的介绍了改进算法的计算过程,证明了改进算法的有效性。     

基于粒子群算法的无人机航迹规划问题

文章首先将无人机航迹问题转换为多目标的，TSP问题数学模型，建立了航运规划问题的数学模型。然后将轨迹规划问题转换成一个求最短路径的单目标的有约束的优化问题，针对这类问题的求解，采用了一种新的粒子群算法并利用软件编程求解。最后验证了结果的可行性，同时讨论了结果的稳定性和收敛性。     

发达网络环境下军用油料运输路径选择研究

对军事油料运输的特点进行了分析,筛选出了影响军用油料运输决策的主要目标:运输时间、可靠性、安全性。并考虑在发达的运输网络情况下,解决基于多目标的油料运输路径选择优化问题。     

城市垃圾运输处理中运输规划的研究现状与方向

从运输问题的性质来看,城市垃圾运输处理问题应属于废弃物流问题的一种,同时也是一种多目标、多层次、有特殊约束的运输问题。传统对城市垃圾的研究基本都集中在末端治理和源头控制,以研究垃圾处理模型为主。本文结合国内外有关垃圾处理的文献,对城市垃圾处理的运输路线、第三方物流运输模式、运输处理算法和模型建立以及回收运输网络系统等方面进行了论述,同时针对城市生活垃圾处理站选址优化、物流系统优化等问题提出了合理的对策和建议。     

运输能力限制条件下的煤炭物流路径选择

针对保障电厂用煤安全这一关系生产生活用电的重大问题,从标准运输问题模型出发,结合电力企业的实际情况,将多目标运输模型应用于煤炭运输问题,并针对接近或达到饱和的线路设定运力限制约束条件,建立运力限制下的多目标运输模型。通过实例分析运用Lingo软件对模型进行求解,验证了模型在解决运输能力限制条件下煤炭物流路径选择中的应用性,可为电力企业制定或优化煤炭调运方案提供依据。     

基于TOPSIS法的天然气集输管网规划方案决策

天然气集输管网系统庞大而复杂,而管网最优规划是在气田开发地面工程建设中必须首先解决的问题。本文采用TOPSIS多目标决策法对天然气集输管网工程的规划方案集进行评价,并首次在方案整体评价中把环境条件(如穿越河流、穿越公路、管线护坡工程)对投资、施工、管理的影响综合进行考虑。用该方法对实例中的8个预选方案进行综合评价,选出了技术上可行、经济上合理、符合工程要求的最佳规划设计方案。     

Service load balancing,task scheduling and transportation optimisation in cloud manufacturing by applying queuing system

Recently, there is a great deal of attention in Cloud Manufacturing (CMfg) as a new service-oriented manufacturing paradigm. To integrate the activities and services through a CMfg, both Service Load balancing and Transportation Optimisation (SLTO) are two major issues to ease the success of CMfg. Based on this motivation, this study presents a new queuing network for parallel scheduling of multiple processes and orders from customers to be supplied. Another main contribution of this paper is a new heuristic algorithm based on the process time of the tasks of the orders (LBPT) to solve the proposed problem. To formulate it, a novel multi-objective mathematical model as a Mixed Integer Linear Programming (MILP) is developed. Accordingly, this study employs the multi-choice multi-objective goal programming with a utility function to model the introduced SLTO problem. To better solve the problem, a Particle Swarm Optimisation (PSO) algorithm is developed to tackle this optimisation problem. Finally, a comparative study with different analyses through four scenarios demonstrates that there are some improvements on the sum of process and transportation costs by 6.1%, the sum of process and transportation times by 10.6%, and the service load disparity by 48.6% relative to the benchmark scenario.     

配送中心选址问题研究文献综述

通过研究、分析、归纳和总结国内外配遥中心选址问题研究文献,提出新的分类法。即单独研究配送中·心选址问题类和结合物流管理的库存战略、运输战略、顾客服务目标等其它战略研究配送中心选址问题类。根据列举、剖析两类文献中的典型文献和分析物流配送业的新趋势、新发展,提出配这中心选址问题研究的新方向——基于顾客满意度的多目标配送中心选址问题。     

考虑碳排放因素的车辆路径问题研究

将碳排放因素考虑到车辆路径问题中,建立了运输成本与碳排放相结合的多目标车辆路径问题模型,讨论了基于改进遗传算法的车辆路径问题的设计和实现,最后通过实例分析对模型作了进一步验证。     

Bi-criteria solid transportation problem with substitutable and damageable items in disaster response operations on fuzzy rough environment

Successful planning and scheduling of relief operations play a key role in saving lives and reducing damage in disasters. These disaster operations involve a variety of challenging multi-objective optimization problems, for which soft computing methods are well suited. In this investigation, relief materials and human resources are transported from some distribution centers (DCs) to some delivery points (DPs) through conveyances. The objectives are to minimize both total cost and time for transportation. Some particular models for (a) substitutable items (b) damageable items and (c) safety Factor have been derived. To convert bi-criteria solid transportation problem into a single objective problem, three different techniques (i) Fuzzy interactive satisficing method, (ii) Global Criterion Method and (iii) Convex Combination Method are used. Then the reduced single objective problem is solved by a non-linear optimization technique – Generalized reduced gradient method using LINGO-14.0. The models are illustrated through some numerical examples and optimal results are presented in tabular forms.     

A new three-dimensional manufacturing service composition method under various structures using improved Flower Pollination Algorithm

With the growing complexity of customer requirements and the increasing scale of manufacturing services, how to select and combine the single services to meet the complex demand of the customer has become a growing concern. This paper presents a new manufacturing service composition method to solve the multi-objective optimization problem based on quality of service (QoS). The proposed model not only presents different methods for calculating the transportation time and transportation cost under various structures but also solves the three-dimensional composition optimization problem, including service aggregation, service selection, and service scheduling simultaneously. Further, an improved Flower Pollination Algorithm (IFPA) is proposed to solve the three-dimensional composition optimization problem using a matrix-based representation scheme. The mutation operator and crossover operator of the Differential Evolution (DE) algorithm are also used to extend the basic Flower Pollination Algorithm (FPA) to improve its performance. Compared to Genetic Algorithm, DE, and basic FPA, the experimental results confirm that the proposed method demonstrates superior performance than other meta heuristic algorithms and can obtain better manufacturing service composition solutions.     

基于模糊熵和多目标规划的公路货运交通枢纽布局模型

针对货运交通枢纽布局问题,首先利用模糊熵获得指标的权重,集结指标值后得到备选交通枢纽的综合评价值,建立一个多目标规划模型来最小化交通成本,最大化建设枢纽的综合评价值,求解后确定货运枢纽的位置、数量、容量等级。     

震后模糊道路破损率条件下应急物资调配研究

应急物资调配是应急物流系统重要研究问题之一,直接关系到应急物流活动的成败。考虑到灾后运输道路破损率不能立即确定,构建了道路破损率与物资需求量为梯形模糊数的多目标应急物资调配模型。通过将其转化为具有确定系数的多目标规划模型来进行求解,并提出了求得该模型满意解的算法。最后通过算例分析说明该方法的有效性。