邮政运输网络中的邮路规划和邮车调度

根据不同情况的要求,采用多种算法来确定邮路规划.1)按照邮车不超载的要求,提出改进型贪心算法,得到符合条件的邮路规划,并结合实际,进一步提出改进方案.2)依据最小生成树理论,提出对各支局进行初步分组方法.同时,基于Floyd算法,提出了改进型TSP算法,并建立求解最小路径的模型,进而得到最经济的邮路规划.3)根据最佳Hamilton圈的理论,判断支局应归人的邮路,从而达到减少成本的目的.4)利用最短路覆盖中心算法,确定最合适的县局地址,使邮路总成本最小化.     

邮政运输网络中的邮路规划和邮车调整

主要针对我国邮政运输业中邮路规划和邮车调整问题,研究了在规定时间、规定邮车运载能力限制的条件下,单个县级邮区内的最小成本/最小空车率邮路规划以及多个邮区协同规划的策略,提出了一个用于辅助规划的邮路存在性定理,设计并实现了基于最小生成树和TSP的县级邮路规划算法.最后在打破县区行政规划的基础上,对整个市区的支局进行重新划分并求解得到了优于前面邮路规划的新方案.     

邮政运输网络中的邮路规划和邮车调度

本题是一道VRP问题,它涉及到最短路线、最小费用等条件下的优化问题.问题一中,我们论证出最少需要3辆邮车才能满足要求.然后对C1区域根据装载量、时间要求遍历出所有的可行路线,最后选出因空车率而减小的收入最小的邮路,其减少的收入为49.35元.问题二中,将整个区域进行划分,在每个小区域应用分枝定界法求出运行成本的路线.再通过对区域的微调讨论出使邮车数目更小的、更节省运行成本的邮路规划方案.问题三中,由于我们将Z55,Z57由县局X1负责运送,Z27由县局X2负责运送.问题四是一个选址问题.我们借助于中心点算法,考虑各支局在本县区域内的位置,并结合与地市局的距离,提出了相应的选址方案.     

邮政运输中邮路的规划和邮车调度问题的研究

以邮政运输网络中运输效益最优为目标,建立了分步规划的图论模型.运用Floyd算法、Kruskal算法对模型进行分步求解并逐步优化,通过Matlab、Lingo、SPSS软件求解,提出三种优化邮路、降低邮车调度成本的方法.模型对解决邮路问题、单旅行商、多旅行商等相关问题具有普遍适用性,可以推广到点数更多TSP的问题.     

乘用车物流运输计划问题的建模研究

首先针对不同类型、数量乘用车的物流运输问题,构建整数线性规划模型,并对模型进行逐层优化求解,通过MATLAB编写通用程序实现计算;在此基础之上,为解决不同目的地的运输要求,采用启发式逐层优化算法进行求解;最后考虑多因素的实际问题,建立分层划分模型,提出构造型分层划分启发式算法求解.计算表明,所建模型计算结果良好,实现了对乘用车物流运输计划问题的优化.     

一类树图的最短路的算法

本文研究了边点赋权图、顶点关于图的运输量及质心,利用比较两个相邻顶点的运输量的方法,得到了一个连通树图的顶点是质心的充要条件及质心个数不大于2的结果.同时给出了求质心及最小运输量的算法,其算法的时间复杂度为O(n2),有利于可建立树图模型的优化问题的求解.     

最小权点覆盖问题的一个近似算法

在点、边赋权的简单图中,关于最小权点覆盖问题,以经典的最短路算法-Dijkstra算法为基础,提出了一个求解该问题的近似算法.首先,在给定的赋权图中任选一点作为初始点,并给出允许集及相关定义.然后,利用经典的最短路算法-Dijkstra算法,求出初始点到允许集中各顶点的最短路径,并按照一定的原则选择近似最小权点覆盖集.最后,通过算例阐释了算法的实现过程的合理性及有效性.     

求解最大割问题的半定规划松驰的序列线性规划方法

本文基于最大割问题的半定规划松弛,利用矩阵分解的方法给出了与半定规划松弛等价的非线性规划模型,提出一种序列线性规划方法求解该模型.并在适当的条件下,证明了算法的全局收敛性.数值实验表明:序列线性规划方法在时间上要优于半定规划的内点算法.所以序列线性规划方法能更有效地求解大规模的最大割问题的半定规划松弛.     

以能耗最低为目标的列车调控方案研究

研究的是以能耗最低为目标的单、多列车优化调控方案问题.首先根据列车运行的各个阶段的分析,构建以运行能耗最低为目标的非线性规划模型,采用逐步迭代算法进行求解,得到的最佳运行模式为无惰行运行,相应的最小能耗为12.47kwh.对于无高峰期的多列车节能运行控制问题,建立了以回收能量最多为目标的0-1非线性规划模型,得到发车间隔为578.86s、575.59s和760.89s,并以此规律循环33轮的发车间隔时间表,使得能量回收最大为250.57kwh,回收率为19.66%.对于存在早晚高峰的情形,建立了以回收能量最多为目标的5阶段0.1非线性规划模型,求出了全天的最优发车方案.     

装载与运输路径的联合最优规划

运输问题中可以分为两个过程:分配装载和规划路径运输,后者是图论问题,前者因为涉及到分配不同的货物装载到不同的运输工具上,是非线性整数规划问题,所以整个问题也是NP复杂问题,随着问题复杂度的增加,变量增多,求解将会非常耗时和困难.提出了基于多旅行商的M-TSP图论装载运输优化模型,和对此模型进行简化后的基于确定路线的整数线性规划装载模型,从而极大的方便此类问题的快速求解,为实际生产运输商业行为提供了一种方便、科学、可靠的决策模型和方案.     

Integer programming formulations for the minimum weighted maximal matching problem

Given an undirected graph, the problem of finding a maximal matching that has minimum total weight is NP-hard. This problem has been studied extensively from a graph theoretical point of view. Most of the existing literature considers the problem in some restricted classes of graphs and give polynomial time exact or approximation algorithms. On the contrary, we consider the problem on general graphs and approach it from an optimization point of view. In this paper, we develop integer programming formulations for the minimum weighted maximal matching problem and analyze their efficacy on randomly generated graphs. We also compare solutions found by a greedy approximation algorithm, which is based on the literature, against optimal solutions. Our results show that our integer programming formulations are able to solve medium size instances to optimality and suggest further research for improvement.     

On some balanced, totally balanced and submodular delivery games

This paper studies a class of delivery problems associated with the Chinese postman problem and a corresponding class of delivery games. A delivery problem in this class is determined by a connected graph, a cost function defined on its edges and a special chosen vertex in that graph which will be referred to as the post office. It is assumed that the edges in the graph are owned by different individuals and the delivery game is concerned with the allocation of the traveling costs incurred by the server, who starts at the post office and is expected to traverse all edges in the graph before returning to the post office. A graph G is called Chinese postman-submodular, or, for short, CP-submodular (CP-totally balanced, CP-balanced, respectively) if for each delivery problem in which G is the underlying graph the associated delivery game is submodular (totally balanced, balanced, respectively). For undirected graphs we prove that CP-submodular graphs and CP-totally balanced graphs are weakly cyclic graphs and conversely. An undirected graph is shown to be CP-balanced if and only if it is a weakly Euler graph. For directed graphs, CP-submodular graphs can be characterized by directed weakly cyclic graphs. Further, it is proven that any strongly connected directed graph is CP-balanced. For mixed graphs it is shown that a graph is CP-submodular if and only if it is a mixed weakly cyclic graph. Finally, we note that undirected, directed and mixed weakly cyclic graphs can be recognized in linear time. Received May 20, 1997 / Revised version received August 18, 1998?Published online June 11, 1999     

钢管的订购和运输

本文先利用问题一中铺设线路无分岔的特点 ,建立了基于图解法的最小面积模型 ,将规划问题转化为使若干折线段下方面积和最小的问题 ,通过简单的判别准则 ,手工求得最小总费用为 1 2 78631 .6万元 ,并对该结果最优性进行了说明 .对问题三参考网络流思想建立了适用于一般铺设路线的非线性规划模型 ,用SAS得到一个最优方案和最小费用 1 4 0 6631 .4万元 ,并用此模型对问题一的灵敏度进行了准确的定量分析 .     

工件优先级图为非连接图且含环的单机总加权拖期调度问题

为满足实际生产环境对工件加工顺序和工件到达时间的要求,提出了具有新特征的单机总加权拖期调度问题,其特点体现在:工件有动态到达时间,且由工件优先级关系构成的优先级图为非连接图且存在环的情况,对该问题建立数学规划模型,在扩展Tang和Xuan等的基础上,提出了结合双向动态规划的拉格朗日松弛算法求解该问题。在该算法的设计中,提出双向动态规划算法求解拉格朗日松弛问题,使得它可处理优先级图中一个工件可能有多个紧前或紧后工件的情况,采用次梯度算法更新拉格朗日乘子,基于拉格朗日松弛问题的解设计启发式算法构造可行解。实验测试结果显示,所设计的拉格朗日松弛算法能够在较短的运行时间内得到令人满意的近优解,为更复杂的调度问题的求解提供了思路。     

Covering partially directed graphs with directed paths

We consider graphs which contain both directed and undirected edges (partially directed graphs). We show that the problem of covering the edges of such graphs with a minimum number of edge-disjoint directed paths respecting the orientations of the directed edges is polynomially solvable. We exhibit a good characterization for this problem in the form of a min-max theorem. We introduce a more general problem including weights on possible orientations of the undirected edges. We show that this more general weighted formulation is equivalent to the weighted bipartite b-factor problem. This implies the existence of a strongly polynomial algorithm for this weighted generalization of Euler's problem to partially directed graphs (compare this with the negative results for the mixed Chinese postman problem). We also provide a compact linear programming formulation for the weighted generalization that we propose.     

Cost allocation in the Chinese postman problem

This paper considers a cost allocation problem that arises from a delivery problem associated with the Chinese postman problem (CPP). A delivery problem is described by a connected undirected graph in which each edge belongs to a different player, a cost function on the edges of this graph and a fixed vertex which is referred to as the post office. Assume that the post office is providing some service to the players. The nature of this service, which can be thought of as mail delivery, requires that a server will travel along the edges of the graph and returns to the post office. The cost allocation problem is concerned with the cost of providing the service to all players. A specific cost allocation rule is introduced and characterized. Further, the class of delivery problems gives rise to a new class of cooperative combinatorial optimization games called delivery games. It is shown that the outcome of the allocation rule with respect to a bridge-connected Euler graph is a core element of the corresponding delivery game.     

The freight allocation problem with lane cost balancing constraint

We consider a problem faced by a buying office for one of the largest retail distributors in the world. The buying office plans the distribution of goods from Asia to various destinations across Europe. The goods are transported along shipping lanes by shipping companies, many of which have collaborated to form strategic alliances; each lane must be serviced by a minimum number of companies belonging to a minimum number of alliances. The task involves purchasing freight capacity from shipping companies for each lane based on projected demand, and subject to minimum quantity requirements for each selected shipping company, such that the total transportation cost is minimized. In addition, the allocation must not assign an overly high proportion of freight to the more expensive shipping companies servicing any particular lane, which we call the lane cost balancing constraint.This study is the first to consider the lane cost balancing constraint in the context of freight allocation. We formulate the freight allocation problem with this lane cost balancing constraint as a mixed integer programming model, and show that even finding a feasible solution to this problem is computationally intractable. Hence, in order to produce high-quality solutions in practice, we devised a meta-heuristic approach based on tabu search. Experiments show that our approach significantly outperforms the branch-and-cut approach of CPLEX 11.0 when the problem increases to practical size and the lane cost balancing constraint is tight. Our approach was developed into an application that is currently employed by decision-makers at the buying office in question.     

一种改进的公交网络最优路径算法

通过对公交网络模型进行分析,考虑公交线路票价变化,按照出行时间最短同时保证换乘次数较少的原则,对现有解决公交网络最短路问题的算法进行改进.应用了将公交线路抽象为顶点,建立邻接矩阵的方法处理换乘问题.通过实际问题计算验证了算法的有效性.     

An Algorithm for Solving the Shortest Path Improvement Problem on Rooted Trees Under Unit Hamming Distance

Shortest path problems play important roles in computer science, communication networks, and transportation networks. In a shortest path improvement problem under unit Hamming distance, an edge-weighted graph with a set of source–terminal pairs is given. The objective is to modify the weights of the edges at a minimum cost under unit Hamming distance such that the modified distances of the shortest paths between some given sources and terminals are upper bounded by the given values. As the shortest path improvement problem is NP-hard, it is meaningful to analyze the complexity of the shortest path improvement problem defined on rooted trees with one common source. We first present a preprocessing algorithm to normalize the problem. We then present the proofs of some properties of the optimal solutions to the problem. A dynamic programming algorithm is proposed for the problem, and its time complexity is analyzed. A comparison of the computational experiments of the dynamic programming algorithm and MATLAB functions shows that the algorithm is efficient although its worst-case complexity is exponential time.     

Cutting plane algorithms for solving a stochastic edge-partition problem

We consider the edge-partition problem, which is a graph theoretic problem arising in the design of Synchronous Optical Networks. The deterministic edge-partition problem considers an undirected graph with weighted edges, and simultaneously assigns nodes and edges to subgraphs such that each edge appears in exactly one subgraph, and such that no edge is assigned to a subgraph unless both of its incident nodes are also assigned to that subgraph. Additionally, there are limitations on the number of nodes and on the sum of edge weights that can be assigned to each subgraph. In this paper, we consider a stochastic version of the edge-partition problem in which we assign nodes to subgraphs in a first stage, realize a set of edge weights from a finite set of alternatives, and then assign edges to subgraphs. We first prescribe a two-stage cutting plane approach with integer variables in both stages, and examine computational difficulties associated with the proposed cutting planes. As an alternative, we prescribe a hybrid integer programming/constraint programming algorithm capable of solving a suite of test instances within practical computational limits.