Solving the generalized transportation problem

This paper advocates a mathematical programming approach for solving the classical transportation problem generalized to include non-linear demand and supply functions and non-linear transport costs. Such an approach is made possible by the recent public availability of a powerful optimizing system called MINOS, assembled for the solution of large programming problems for which the constraint set is linear and spatial. Primal and dual program formulations for this generalized transportation problem are set out in the paper, and brief computational experience with the software system in solving several illustrative problems is recorded.     

Multiplant MRP

Many manufacturing firms have multiple manufacturing plants, located in geographically diverse parts of the world. This situation is becoming more common, as firms establish new plants in foreign countries to take advantage of low labor cost. In such cases, it is not unusual for the firm to retain production capability of certain key parts in a backup plant, with the necessary equipment and trained workforce in place. High volume production could be obtained relatively quickly from the backup plant in case of an emergency at the main supplying plant. In such multiplant settings, the transportation costs are significant. Throughout this paper, we use the term “multisourced parts” to describe parts produced in more than one location.Material Requirements Planning (MRP) is the component of a total manufacturing control system that is designed to manage inventory and plan orders for parts and material with dependent demand (demand derived from the demand of other items). Most of the literature on MRP systems discusses MRP methodology in a single-plant environment. Most MRP software systems in use today are single-plant systems.Currently, it is common for firms with multiple plants treated as cost centers to use an independent single-plant MRP system for each and handle the transshipment problems manually. Because of lack of coordination of production schedules between supplying and demanding plants, those firms hold more inventory and experience longer lead times than necessary to compensate for uncertainties in schedules and supply policies.The purpose of this article is to enhance single-plant MRP systems for coping with multiplant situations in which: the plants are regarded as cost centers, there exist multisourced parts, and the transportation costs are significant. The multiplant MRP system should recognize that parts are produced in different plants, make offset calculations for in-transit lead times, and consider transportation costs when establishing production requirements and shipping routes for multisourced parts. The objective is, beginning with the corporate-determined master schedule for finished products, to communicate in one planning cycle time-phased planned order release schedules and shipping/delivery schedules to each manufacturing plant producing components for the finished products.We first present a simplified framework for the multiplant MRP system, where a transportation algorithm is incorporated into the MRP logic. Then we refine this simplified framework to handle more complex aspects of a multiplant network. These complexities include the treatment of requirements that are not shipped on time and the regeneration of new MRP schedules. We also observe that the solution to the transportation problem described above is affected by the lot-sizing rules employed. In addition, we discuss several important issues and decisions that confront a firm when implementing a multiplant MRP system.     

运输需求理论综述

运输需求是运输市场结构的重要组成部分之一,它与运输供给是辩证统一的关系。运输需求是产生运输供给的原因,运输需求必须要通过运输供给才能得以实现。本文主要是在前人研究的基础上对运输需求理论进行综述。     

Goal programming solutions to transportation problems with variable supply and demand requirements

This article deals with goal programming as an aid to resolving transportation problems. The objective of this study is to demonstrate the use of goal programming as an approach to reducing total cost in transportation problems that possess variable supply and demand requirements. A generalized goal programming model is formulated and applied to a series of transportation problem situations based on the empirical data provided by a medium-size trucking firm. Comparison of the results demonstrates the cost advantage of using the goal programming model in place of the transportation method and integer interval linear programming.     

Optimal locations and flow allocations for aggregation hubs in supply chain networks of perishable products

Establishment of aggregation hubs in a supply chain network (SCN) is typically a facility location-allocation (FLA) decision, which is known to be a NP-hard optimization problem. Considering the flow of heterogeneous perishable products, like fresh produce, with different spoilage rates, further increases the complexity of such a problem. This is due to the effect of transportation time and conditions, services provided in the hub, and hub proximity to supply sources, on the quality and quantity of products eventually reaching the demand destinations, and hence on the location-allocation decision. In this paper, this problem is formulated as a mixed integer linear programming (MILP) model that considers a number of problem characteristics simultaneously for the first time, to minimize the transportation, spoilage, processing, and capacity-based hub establishment costs. Due to its complexity, two hybrid algorithms that combine a meta-heuristic with a perishability-modified transportation algorithm, are proposed to solve the problem. The algorithms are based on binary particle swarm optimization (BPSO) and simulated annealing (SA). Taguchi analysis is used to tune the significant parameters of both algorithms considering different problem sizes. Computational analysis is further conducted to evaluate and compare the performances of the algorithms using randomly generated test instances and exact solutions obtained using CPLEX. Results show that while both algorithms are capable of obtaining optimum solutions for most instances, the hybrid BPSO slightly outperforms the hybrid SA in terms of consistency and solution time.     

基于Floyd算法的供应链网络路径研究

21世纪的竞争不是企业与企业之间的竞争，而是供应链之间的竞争。运输系统是供应链中一个重要的子系统，运输路径的选择是否合理直接影响供应链的运作成本、速度和效益。文中考虑在拉动式生产的背景下，当销售商提出需求订单的时候，最快的选择相应的制造商和配送中心，使得供应链的总运输成本最小化的问题，利用floyd算法研究三级供应链的运作模式，理论证明其可行性，并通过算例分析验证了此优化算法使得供应链运输成本最小化。     

基于多种运输方式的第四方物流路径问题研究

建立了基于多种运输方式的第四方物流路径优化模型,通过虚拟运输网络,将第四方物流路径问题转化为一个带时间约束和能力约束的最短路径问题,并给出了基于Dijkstra的启发式算法。算例显示,该算法能方便有效地求解基于多种运输方式的第四方物流路径问题。     

Location-allocation problem for intra-transportation system in a big company by using meta-heuristic algorithm

This paper presents the location-allocation problem of parking facilities in Mobarakeh Steel Company. The aim is to find the optimal location for the parking facilities and allocate travels between departments to each parking facility. To optimize the cost and facing the transportation demands of all departments, a mathematical model is designed and solved by a commercial software package. Also, the number of vehicles allocated to each parking facility is determined. A hybrid meta-heuristic algorithm combining a genetic algorithm with parallel simulated annealing is developed which can be used even in more complicated structure of the problem. The results show that this hybrid algorithm is highly efficient in solving this kind of problems.     

战时装备保障的多目标运输问题及其求解

提出了集中考虑时间性，安全性的战时装备保障的多目标运输问题并建立了该运输问题的数学模型。基于一种二次抛物偏大型分布的模糊规划算法，将多目标运输问题转化为单目标运输问题，并通过一种改进的表上作业法求得最做优折衷解。最后给出一个实例， 验证了方法的有效性。     

基于供应链视角的乳制品质量安全问题研究

乳制品作为日常生活的必需品,其质量安全得到人们的普遍关注。乳制品供应链的任一环节出现问题,都将会严重影响乳制品的质量安全。从供应链角度出发,探讨了奶农饲养、原奶收购、运输和贮存、乳制品加工、乳制品运输和销售等环节可能存在的安全问题,为乳制品质量安全的发展提供理论依据。     

基于Extendsim的多级库存系统仿真

针对多级库存难以控制的问题,利用Extendsim软件对需求和提前期均随机的多级库存系统进行建模和仿真,以供应链的利润最大化为目标,结合该软件的Optimizer模块,对多级库存各节点的订货点、订货量进行遗传算法计算。从而有效地解决了多级库存难以管理的问题。     

我国铁矿石码头布局现状分析

通过对我国铁矿石码头供需及布局现状的分析．总结出我国铁矿石码头布局存在着码头总体接卸能力不足、大型铁矿石专用码头不足、码头集疏运能力仍需改善三个主要问题．这对于解决目前我国进口铁矿石港口积压问题,降低铁矿石运输成本．满足未来我国进口铁矿石运输条件具有十分重要的意义．同时也为我国未来矿石码头的建设和布局规划提供了重要的理论依据。     

基于免疫算法的后方仓库选址建模与仿真

针对当前陆军装备维修器材供应链后方仓库供应网络布局不合理、保障效益低等问题,建立后方仓库选址非线性规划模型,设计免疫算法仿真求解。以NB战区为例,验证了模型和算法的有效性,得到后方仓库最佳位置和供应网络,为全面、科学做出后方仓库选址决策供定量分析数据支撑和可视化图形参考,并与粒子群算法和遗传算法进行对比分析。     

供应链管理中的两层规划算法

文章概述两层规划问题在交通领域、资源分配、委托代理以及供应链管理中的应用并讨论了线性和非线性两种两层规划问题,总结了极点算法、下降迭代、惩罚函数和分支定界算法,并进行了评价,最后进一步探讨了两层规划问题的应用前景和算法的发展方向。     

多式联运环境下带时间窗的多产品运输问题研究

多式联运环境下带时间窗的路径选择问题是广泛应用于物流配送领域的一类组合优化问题,然而目前相关研究主要聚焦于多式联运环境下单个起点到单个终点的一种货物配送问题,其研究成果难以直接适用于汽车销售、钢铁运输等环境下单个供货商到多个零售商的多产品运输问题。因此,文中以汽车销售为研究背景,对多式联运环境下带时间窗的多产品运输问题进行研究,建立了该问题的数学模型,然后利用蚁群算法进行了求解,最后通过实验验证了算法的有效性。     

新时期完善我国房地产市场体系研究

由于我国住房供给制度不够完善,致使住房供给和需求不匹配。高收入者能够购买多套住房,而低收入者却买不起房,只能借助于住房保障体系解决居住问题。由于国内外多种因素的影响,市场商品房价格不断提高。政府若能积极完善好住房保障体系,便能解决社会中大多数低收入者的住房问题,逐步下降商品住房房价。本文认为,我国房地产市场的主要问题是供给和需求体系的不匹配,社会低收入者住房保障不够完善。故此总结了新时期我国房地产市场发展的新问题,并深入分析了房地产市场体系中的缺陷,提出了完善房地产市场体系的措施和方法。     

Two-level national-regional planning and mathematical programming decomposition applied to spatial price equilibrium models2

This paper is concerned with computation strategies related with the quantitative analysis of only a sector of a global economy (e.g. agriculture or energy). Under a ceteris paribus condition on the environment of the sector, and within the hypothetical context of the neoclassical economic theory, it is well known a type of partial equilibrium model that can be cast mathematically into an optimization framework. We attempt here to a typical specification which considers spatially separated markets, that has been called spatial price equilibrium model and that has contained within it many classical transportation problems (one for each commodity). The model is specially suitable for mathematical programming decomposition, resulting regional sybsystems whose coupling variables are the transportation flows. We explore here this structure, discussing two decomposition algorithms with economic interpretations that suggest decentralized procedures for planning. The first—of the price coordination type—is a variant of the Dantzig-Wolfe's principle which is expected to have a low number of cycles of information flow between the master level and the sub-problems (at each cycle it is calculated a series of regional production-consumption responses to alternative prices generated by transhipment problems at the central planning level). The second algorithm specializes the Geoffrion's projection/feasible directions technique, so interpreting the problem solution within the context of a net-output target coordination.     

上海市住房有效供给对策研究

从土地供给和房地产开发两方面着手，对上海市住房供给的有效性进行定量分析。土地供给方面主要是：土地供给，总量相对需求不足、供给结构失衡和土地闲置等问题。房地产开发方面则有：投资结构单一、开发档次不合理和住宅施竣比畸高等问题。因而，研究者从制度角度、开发角度和需求角度三方面研究阐述了提高住房供给有效性的对策与建议。     

遗传算法在现代物流系统中的应用研究

遗传算法是一种基于自然进化原理的全局搜索随机算法。通过遗传算法特点的介绍,阐述了物流规划中的相关问题。研究了遗传算法在选址问题、配送问题、调度问题、运输问题、布局问题等问题中的应用方法,介绍了其理论价值,及对实际工作的指导作用。     

浅谈城市市政给排水的规划设计

"水资源"、"水环境"、"水灾害"这三大问题关系到城市的进一步发展,编制城市给排水规划时妥善处理好城市发展中可能面临的水资源、水环境、水灾害问题,以节能和发展为主要理念,高质量地编制好城市给排水规划,为城市实现可持续发展提供基础和保障。