C运输问题

在传统的运输问题中 ,总假设所有产地 (发点 )的产量之和或所有销地 (收点 )的销量之和就是货物的总运输量 .但在实践中 ,特别是在一些与环境有关的资源、稀有资源或不可再生资源的开发利用过程中 ,由于受环境保护或政策限制 ,常常对这些资源的开采和运输有一定的数量限制 .这一类对总运输量有数量限制的运输问题不同于 A运输问题和 B运输问题 ,我们把它称为 C运输问题 .事实上 ,C运输问题是 A运输问题和 B运输问题的推广 .将给出 C运输问题的数学模型和求解方法 .     

钢管订购与运输问题三的数学模型与灵敏度分析

本文针对 2 0 0 0年全国大学生数学建模竞赛 B题——钢管订购与运输问题的问题 ( 3) ,建立了数学模型 ,给出了该数学模型的精确求解 .然后对问题 ( 1 )与问题 ( 3)给出了灵敏度分析 .     

具有模糊信息的多目标运输问题求解

提出一种求解具有模糊信息的多目标运输问题的方法。利用专家意见通过模糊算法集给从各产地到各目的地运送单位物资的模糊综合指标值,运用一种对模糊数排序的方法,将模糊多目标运输问题转化为单目标的运输问题进行求解,最后给出了一个数值例子。     

运筹学中几种运输问题的求解方法探析

从目前研究生入学考试中出现的几种新的运筹学运输问题出发,探讨了各种运输问题与传统运输问题的差异。提出以传统运输问题为本,将非传统运输问题转化为传统运输问题借助表上作业法求解的思路。并针对6种不同的非传统运输问题分析了转化的过程和步骤,为运输问题的研究提供了新的内容.     

一种求解救灾物资运输问题的改进解法

本文通过对B运输问题建立数学模型,提出了一种求解B运输问题的改进解法。改进解法首先通过最小元素法求出初始解,然后进行变量闭回路法调整,直到求出最优解,并给出了一个计算实例证明了解法的有效性。文章还对改进解法和另外两种现有的算法进行了综合的分析,由于改进解法计算过程中采用的变量闭回路法省略了求检验数的环节,使得新算法比两种现有的算法更简便。     

一种运用Vague集理论转化区间运输规划的方法

为解决区间型运输问题的清晰化处理问题,将Vague集当中真假隶属度函数与必要性测度和可能性测度有机的联系起来;将区间型运输问题的约束条件分为两大类等价的问题进行研究;针对供需区间型运输规划问题的特点,利用截集的思想实现了不确定性运输问题向确定性运输问题的转化.     

平衡和不平衡运输问题与分配问题的通用迭代算法

将不平衡运输问题转化成网络最短路问题,利用Floyd算法规则,给出了一种既可以解平衡和不平衡运输问题,又可以解平衡和不平衡分配问题的通用迭代算法。与专门用于解运输问题的闭合回路法和专门用于解分配问题的匈牙利法相比,这种算法不但具有通用的优点,而且更便于在计算机上运行。     

广义指派问题

广义指派问题可以表述为：指派ｍ位人员执行ｎ项任务,指派人员ｉ执行任务ｊ的收益为ｃｉｊ,需指派人员ｉ执行ａｉ至ａｉ项任务和ｂｊ至ｂｊ位人员执行任务ｊ,问如何指派使总效益最优。广义指派问题可以转化为一个能用对偶运输解法求解的容量运输问题     

运输问题悖论及其研究

提出了运输问题的奇特现象——运输问题的悖论,讨论了运输问题悖论出现的条件,最后指出了研究运输问题悖论的现实意义.     

多目标运输问题的Fuzzy线性规划解法

经典运输问题是一类特殊的单目标线性规划问题，可用表上作业法或单纯形法求其最优解。近年来，许多学研究了多目标运输问题，提出了相应的求解算法。本应用Fuzzy线性规划的方法，给出了多目标运输问题的又一求解算法。     

A new method for solving fuzzy transportation problems using ranking function

In the literature, several methods are proposed for solving transportation problems in fuzzy environment but in all the proposed methods the parameters are represented by normal fuzzy numbers. [S.H. Chen, Operations on fuzzy numbers with function principal, Tamkang Journal of Management Sciences 6 (1985) 13–25] pointed out that in many cases it is not to possible to restrict the membership function to the normal form and proposed the concept of generalized fuzzy numbers. There are several papers in the literature in which generalized fuzzy numbers are used for solving real life problems but to the best of our knowledge, till now no one has used generalized fuzzy numbers for solving the transportation problems. In this paper, a new method is proposed for solving fuzzy transportation problems by assuming that a decision maker is uncertain about the precise values of the transportation cost, availability and demand of the product. In the proposed method transportation cost, availability and demand of the product are represented by generalized trapezoidal fuzzy numbers. To illustrate the proposed method a numerical example is solved and the obtained results are compared with the results of existing methods. Since the proposed method is a direct extension of classical method so the proposed method is very easy to understand and to apply on real life transportation problems for the decision makers.     

A general model for cyclic machine scheduling problems

A general framework for modeling and solving cyclic scheduling problems is presented. The objective is to minimize the cycle time. The model covers different cyclic versions of the job-shop problem found in the literature, robotic cell problems, the single hoist scheduling problem and tool transportation between the machines.It is shown that all these problems can be formulated as mixed integer linear programs which have a common structure. Small instances are solved with CPLEX. For larger instances tabu search procedures have been developed. The main ideas of these methods are indicated.     

Coupling ant colony systems with strong local searches

Ant colony system is a well known metaheuristic framework, and many efficient algorithms for different combinatorial optimization problems have been derived from this general framework. In this paper some directions for improving the original framework when a strong local search routine is available, are identified. In particular, some modifications able to speed up the method and make it competitive on large problem instances, on which the original framework tends to be weaker, are described. The resulting framework, called Enhanced Ant Colony System is tested on three well-known combinatorial optimization problems arising in the transportation field. Many new best known solutions are retrieved for the benchmarks available for these optimization problems.     

运输问题的退化解及表解中0元的添加

在运输问题表上作业法中,有时会遇到退化解问题,这样在给调运方案时需要在调运表上添加0元,可是0应添在何处?大多数文献中均未具体给出或给出的结论有误,0元的添加不当有时会导致一系列问题出现,本文将讨论这些问题,且给出一个0元添加的确定的答案.     

A Branch-and-Bound Algorithm to Solve a Multi-level Network Optimization Problem

Multi-level network optimization problems arise in many contexts such as telecommunication, transportation, and electric power systems. A model for multi-level network design is formulated as a mixed-integer program. The approach is innovative because it integrates in the same model aspects of discrete facility location, topological network design, and dimensioning. We propose a branch-and-bound algorithm based on Lagrangian relaxation to solve the model. Computational results for randomly generated problems are presented showing the quality of our approach. We also present and discuss a real world problem of designing a two-level local access urban telecommunication network and solving it with the proposed methodology.     

A simple greedy algorithm for a class of shuttle transportation problems

Greedy algorithms for combinatorial optimization problems are typically direct and efficient, but hard to prove optimality. The paper presents a special class of transportation problems where a supplier sends goods to a set of customers, returning to the source after each delivery. We show that these problems with different objective functions share a common structural property, and therefore a simple but powerful generic greedy algorithm yields optimal solutions for all of them.     

Partially-linear transportation problems

The nonlinear relationship between quantities and the real cost for their transportation causes interest in some nonlinear transportation problems. Partially-linear transportation problems may be successfully applied in economics because every nonlinear function may be approximated by partially-linear functions. In this work we consider transportation problems with partially-linear dependence of the transportation costs and give the necessary and sufficient conditions for local optimality. A constructive method for solving such problems is suggested.     

Parametric Ghost Image Processes for Fixed-Charge Problems: A Study of Transportation Networks

We present a parametric approach for solving fixed-charge problems first sketched in Glover (1994). Our implementation is specialized to handle the most prominently occurring types of fixed-charge problems, which arise in the area of network applications. The network models treated by our method include the most general members of the network flow class, consisting of generalized networks that accommodate flows with gains and losses. Our new parametric method is evaluated by reference to transportation networks, which are the network structures most extensively examined, and for which the most thorough comparative testing has been performed. The test set of fixed-charge transportation problems used in our study constitutes the most comprehensive randomly generated collection available in the literature. Computational comparisons reveal that our approach performs exceedingly well. On a set of a dozen small problems we obtain ten solutions that match or beat solutions found by CPLEX 9.0 and that beat the solutions found by the previously best heuristic on 11 out of 12 problems. On a more challenging set of 120 larger problems we uniformly obtain solutions superior to those found by CPLEX 9.0 and, in 114 out of 120 instances, superior to those found by the previously best approach. At the same time, our method finds these solutions while on average consuming 100 to 250 times less CPU time than CPLEX 9.0 and a roughly equivalent amount of CPU time as taken by the previously best method.     

Analyzing the potential of a firm: an operations research approach

An approach to analyzing the potential of a firm, which is understood as the firm's ability to provide goods or (and) services to be supplied to a marketplace under restrictions imposed by a business environment in which the firm functions, is proposed. The approach is based on using linear inequalities and, generally, mixed variables in modelling this ability for a broad spectrum of industrial, transportation, agricultural, and other types of firms and allows one to formulate problems of analyzing the potential of a firm as linear programming problems or mixed programming problems with linear constraints. This approach generalizes the one proposed by the author earlier for a more narrow class of models and allows one to effectively employ a widely available software for solving practical problems of the considered kind, especially for firms described by large scale models of mathematical programming.     

The Dial-a-Ride Problem (DARP): Variants,modeling issues and algorithms

The Dial-a-Ride Problem (DARP) consists of designing vehicle routes and schedules for n users who specify pick-up and drop-off requests between origins and destinations. The aim is to plan a set of m minimum cost vehicle routes capable of accommodating as many users as possible, under a set of constraints. The most common example arises in door-to-door transportation for elderly or disabled people. The purpose of this article is to review the scientific literature on the DARP. The main features of the problem are described and classified and some modeling issues are discussed. A summary of the most important algorithms is provided.AMS classification: 90B06, 90C27, 90C59