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。     

运输问题的合作对策求解方法

产地间或销地间往往存在竞争,在这种情况下,使用运输问题最优化方法是不合理的。因此,从个体理性的视角提出运输问题的合作对策求解方法,方法将运输问题看作是一个博弈问题,各个产地或销地是博弈的局中人,求解其纳什均衡与纳什讨价还价解。在此基础上,说明了运输问题的非合作形式是一个指派问题,并证明指派问题的最优解是一个纳什均衡点。接着,通过实验验证运输问题的最优解是一个纳什讨价还价解,满足产地或销地的自身利益。在此基础上,针对纳什讨价还价解不唯一的问题,从决策者的视角给出最大可能激励成本的计算方法。最后,为弥补纳什讨价还价解不唯一及纳什讨价还价解不允许出现子联盟的缺陷,给出运输收益分配或成本分摊的Shapely值计算方法。     

广义D运输问题

D运输问题是一类要求将货物在某一个时间以前如数运抵目的地的运输问题,比如节日物资的运输问题.基于物流管理的需要,提出了广义D运输问题.广义D运输问题是各个销地对货物的运抵时间有不同要求,即各个销地对于货物的需求时间不一定相同的一般情况.建立了广义D运输问题的数学模型,引入了可实施解、满意解、最优解等概念,给出了求解方法和一个计算例子.     

关于B运输问题的两点注记

用实例说明 B运输问题和传统运输问题解的区别 .给出了 B运输问题一个定理的证明 ,从而使 B运输问题的有关理论更加完善     

运输问题的改进算法探讨

探讨了运输问题表上作业法初始解的取得和最优解的判断，在一定程度上可以省略表上作业法的方案调整过程，从而简便了求解运输问题的最优解的过程。     

流向受限运输问题的解法及其应用

本文提出一种解流向受限运输问题的算法.首先给出数学模型,利用位势法解普通运输问题的原理,建立了一种改进型位势法解流向受限运输问题.算法包含了解普通运输问题.对算法进行了理论证明后,研制了软件.用软件在微机 IBM-PC/XT 上编制一个全国性的物资调运计划仅用时间2分钟.长期实用证明方法是有效的.该软件已提供物资调运部门使用20个月.     

运输问题求解的一种网络算法

本着重探讨了在网络图上求运输问题的初始解的方法，并指出在求解受时间约束的运输问题时得到的初始解，在很大程度就是该问题的最优解，通过实例说明了该算法。     

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。     

多品种容量运输问题的位势法

运输问题有很广泛的应用,其解法也很多.做为多品种物资容量运输问题,尽管在现实中有极为广泛的应用,但对其算法讨论的却很少.从计算数学角度来看,用线性规划分解原则来处理它,明显是不适宜的;用图论方法解它,也有困难.为此,我们把位势法推广到多品种物资容量运输问题上,并相应地做了必要的理论讨论.     

线性分式运输问题的一个解法

线性分式运输问题是线性分式规划问题的一种特殊情况，通常可以用线性分式规划问题的一般解法来解这类问题，本文针对分式运输问题的特点给出了一种简便的解法．     

流向受限运输问题解法研究

本文讨论了流向受限运输问题虚运价取适当值时,最优解中不含非退化的限制配点,使解法更明确,并改进了模型[1]。     

分派问题保持最优解不变的充分必要条件

进一步讨论了在保持分派问题最优解不变的情况下,效率矩阵元素的变化范围.这些变化范围是保持分派问题最优解不变的充要条件.     

A Linear Programming Model Combining Land Levelling and Transportation Problems

The levelling process of a vast area of land, for irrigation or any other development plan, is usually done in two stages. The first stage starts by determining the levels of the terrain, while the second stage solves the earthwork allocation for the predetermined levels. The most recent attempt, reported in the literature, to find global optimality for this problem was a trial-and-error approach which solves a linear transportation problem for every possible terrain's level and selects the level that results in the lowest transportation cost. This approach, however, being an iterative procedure, can only come closer to the optimum solution depending on how small the iteration steps are, but does not guarantee global optimality. The paper presented here offers a linear programming model that combines the levelling of terrains and the associated transportation in a single linear programming problem, thus guaranteeing global optimality.     

广义指派问题及其在军事装备运输中的推广应用

军事装备中的运输问题复杂多样,如何建立数学模型是寻求优化方案的关键.本文首先将最优线性指派模型推广到广义指派模型并给出其两种算法,其次对带有时间约束的运输问题进行建模,并设法将其转化为广义指派问题来处理,从而为这类运输问题提供了一种有效可行的算法.     

Initial Solutions to Sets of Related Transportation Problems

Where sets of similar transportation problems are solved independently a great deal of information is wasted. A routine which has been used successfully is described; it is for use in conjunction with the Ford and Fulkerson method for solving the transportation problem, and utilizes the information provided by the optimum solution to one problem to give a good initial solution to the later problems.A similar routine could be easily developed for use with the Stepping Stone method.     

A combinatorial approach to level of repair analysis

This paper presents an approach to optimise level of repair decisions taking into account submodular properties of standard life cycle cost functions, which include fixed and variable costs. It proposes an integer programming formulation to solve level of repair problems for multi-echelon multi-indenture level systems. The method converges quickly to the optimum solution relying on heuristics to obtain tight bounds for a subsequent branch-and-bound procedure. A software package called level of repair optimisation model (LOROM) was developed to implement the branch-and-bound method that does not rely on linear programming relaxations. This approach is rather generic and can be applied to a wide class of problems with convex total cost functions such as plant location problems or transportation problems with fixed costs.     

Integer Programming to Minimize Labour Costs

The main purpose of this paper is to demonstrate a real-world application of pure integer programming to find the optimum solution to a labour cost problem. The length of a daily working shift is defined as an integer variable and several shift strategies are analysed to determine the optimum length and shift combinations that satisfy a predicted demand at minimum cost. The state-space model has been used to predict the stochastic behaviour of monthly demands for beer and soft drink. Savings of about 7% of the annual sales have been obtained as a result of implementing the integer programming approach. A numerical example shows that the solution obtained by rounding off the continuous optimal solution does not match with the integer optimal solution. It was also noted that if a rounded-off solution is feasible, then it provides an initial integer solution for the branch-and-bound algorithm that may reduce the computational time.     

满意度优化运输问题

传统运输问题只考虑配送方案的效率, 而不考虑参与者对配送方案的满意度. 通过引入参与者对配送方案的满意度这一概念, 提出了满意度优化运输问题, 构建了以最大化相对公平为目标的满意度优化运输模型, 并证明了: (1) 当运输问题的可行域不空时, 新模型的解集非空; (2) 从满意度的角度来看, 新模型的解是唯一的. 另外, 还给出了新模型的求解方法. 研究结果进一步丰富了运输问题的类型, 可为解决其他类型运输问题提供借鉴.     

Mathematical investigation of the Gerber-Shiu function in the case of dependent inter-claim time and claim size

In this paper we investigate the well-known Gerber-Shiu expected discounted penalty function in the case of dependence between the inter-claim times and the claim amounts. We set up an integral equation for it and we prove the existence and uniqueness of its solution in the set of bounded functions. We show that if δ>0, the limit property of the solution is not a regularity condition, but the characteristic of the solution even in the case when the net profit condition is not fulfilled. It is the consequence of the choice of the penalty function for a given density function. We present an example when the Gerber-Shiu function is not bounded, consequently, it does not tend to zero. Using an operator technique we also prove exponential boundedness.