具有优先约束的单机随机排序问题

讨论工件的加工时间为常数,机器发生随机故障的单机随机排序问题,目标函数极小化工件的加权完工时间和的数学期望最小.考虑两类优先约束模型.在第一类模型中,设工件间的约束为串并有向图.证明了模块M的ρ因子最大初始集合I中的工件优先于模块中的其它工件加工,并且被连续加工所得的排序为最优排序,从而将Lawler用来求解约束为串并有向图的单机加权总完工时间问题的方法推广到机器发生随机故障的情况.在第二类模型中,设工件间的约束为出树优先约束.证明了最大家庭树中的工件优先于家庭树中其它的工件加工,并且其工件连续加工所得到的排序为最优排序并给出了最优算法.     

有根森林优先约束的单机随机排序问题

讨论单机随机排序问题,目标函数为确定工件的排列顺序使工件的加权完工时间和的数学期望最小.设工件间的优先约束为有根森林,机器发生随机故障.对此情况,给出了多项式时间的最优算法.     

恶化率与工件无关的线性加工时间调度问题

讨论恶化率与工件无关的线性加工时间调度问题 .对于工件间具有平行链约束 ,目标函数为极小化最大完工时间的单机问题 ,分别就链不允许中断和链允许中断两种情况给出了最优算法 .对于工件间没有优先约束 ,目标函数为极小化完工时间和的平行机问题 ,证明了工件按基本加工时间不减排列可以得到最优调度 .     

松弛工期窗口指派和截断控制学习效应资源约束单机排序问题

研究松弛工期窗口指派资源约束单机排序问题,决策者需要在一台处理机上连续处理n个独立的任务.每个任务有一个待定的松弛工期窗口,任务的处理时间通过分配资源可控,且是所在位置的递减函数,当函数递减到一定程度时,需要用一个控制参数替换.目的是在可用资源量有限条件下求出任务的处理顺序和工期窗口以及资源分配方案,使得任务中最大费用取最小值.分两步处理:首先将问题转化为非线性凸规划问题,利用凸规划理论求出任务的资源数量;其次通过解指派问题得到任务最优处理顺序,进而求得任务的工期窗口.给出了多项式时间的最优算法,提供一个算例说明算法的有效性和运算过程.     

具有优先约束的不完全恒速机排序问题

讨论了任务具有优先约束的可中断不完全恒速机排序问题,若处理机具有不同开始加工时间的可中断排序问题存在最优算法,则相应的不完全恒速机排序问题也有最优算法。     

具有凸资源约束的单机指数学习效应问题

研究在所有工件的正常加工时间均相同的情况下具有指数学习效应和凸资源约束的单机排序问题.给出了两种模型:在资源消耗总费用有限的情况下,以工件的最大完工时间为目标函数;在工件的最大完工时间有限的情况下,以资源消耗总费用为目标函数.求两种模型下的最优排序和最优资源分配,使得目标函数最小.证明这两个问题都是多项式时间可解的,并给出了相应的算法.     

任务具有优先约束的不完全同速机排序问题

文中讨论了任务具有优先约束的不完全同速机排序问题，对问题Ｐｍ｜ｂｒｋｄｗｎ，ｉｎｔｒｅｅ，ｐｊ＝１｜Ｃｍａｘ给出了最优算法，对问题Ｐｍ｜ｂｒｋｄｗｎ，ｐｒｅｃ，ｐｊ＝１｜Ｃｍａｘ给出了界为２－２ｍ的算法。     

容器约束的吉普问题

研究无容器约束和容器约束的吉普问题.对无容器约束吉普问题,给出单向及往返的最优行驶策略.对容器约束吉普问题,给出单向及往返行驶策略并证明吉普有能力行至无穷远处.在容器约束下,得到吉普最优行驶策略是一个有挑战性的问题.     

极小化最大提前完工费用的可中断排序问题

讨论了带截止期限的$n$个工件在单机上加工,工件间存在优先约束,在允许机器空闲的条件下,确定一个工件的可中断排序,极小化最大提前完工费用.首先考虑两种特殊情形:(1)截止期限相同,存在优先约束;(2)截止期限任意,不存在优先约束.针对两种情形分别给出了时间复杂度为$O(n^2)$的算法.在此基础上,考虑普遍情形,即截止期限任意,存在优先约束,也给出了一个时间复杂度为$O(n^2)$的算法.由于工件不允许延迟,问题可能会无可行排序,需先对问题的可行性进行讨论.     

工件间具有串并有向图约束的单机随机排序问题

研究机器发生随机故障的单机排序问题,其中工件间的优先约束为串并有向图,目标函数为极小化加权完工时间和,证明了此问题多项式时间可解,并给出了多项式时间算法.     

Analagmatic cubics through quadratic involutive transformations (I)

We generalize the precedent study of two particular cubics, related to any given triangle, by the construction of analagmatic class six cubics under a common quadratic involutive transformation referred again to any given triangle. As resume, we point out some insights for future extensions to generalized theories about the cubics.     

A fuzzy mathematical programming approach for cross-sell optimization in retail banking

We consider the problem of selecting the optimal list of customers to target for a cross-sell campaign in a retail bank. Target selection involves taking estimates of several parameters (response propensity, expected volume, expected profit from a customer, etc) and deciding on the list of customers to whom the offer should be sent such that a certain set of business objectives are met/optimized. We discuss some of the issues related to the target selection process, namely those of unreliable estimates and computational complexity of the problem. We propose a fuzzy mathematical programming technique to address these issues. The imprecise parameters and constraints are represented as triangular fuzzy numbers, while the problem of computational complexity is addressed through a group-level formulation. We use an example of a real-life cross-sell problem for a bank to demonstrate the method. We also provide some sensitivity analyses on critical resources.     

Single machine scheduling with resource dependent release times and processing times

We consider the single machine scheduling problem with resource dependent release times and processing times, in which both the release times and processing times are strictly linear decreasing functions of the amount of resources consumed. The objective is to minimize the makespan plus the total resource consumption costs. We propose a heuristic algorithm for the general problem by utilizing some derived optimal properties and analyze its performance bound. For some special cases, we propose another heuristic algorithm that achieves a tighter performance bound.     

A numerical method for solving an optimal control problem with fixed endpoints of trajectories and a convex functional

We propose a numerical method for solving the problem of taking a nonlinear system to the zero state while minimizing a nonnegative convex functional. The particular cases include the problem of minimizing the consumption of resources or energy. The method is based on the maximum principle and approximations of bodies with some families of simplices. The properties of coverings of bodies with simplices enable us to justify the convergence of the method.     

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 .     

Branch and bound based solution algorithms for the budget constrained discrete time/cost trade-off problem

The time/cost trade-off models in project management aim to reduce the project completion time by putting extra resources on activity durations. The budget problem in discrete time/cost trade-off scheduling selects a time/cost mode for each activity so as to minimize the project completion time without exceeding the available budget. There may be alternative modes that solve the budget problem optimally and each solution may have a different total cost value. In this study we consider the budget problem and aim to find the minimum cost solution among the minimum project completion time solutions. We analyse the structure of the problem together with its linear programming relaxation and derive some mechanisms for reducing the problem size. We solve the reduced problem by branch and bound based optimization and heuristic algorithms. We find that our branch and bound algorithm finds optimal solutions for medium-sized problem instances in reasonable times and the heuristic algorithms produce high quality solutions very quickly.     

A Stackelberg equilibrium for a missile procurement problem

This paper deals with a procurement problem of missiles involving the efficient assignment of the missiles to some targets. Within a fixed amount of budget, a leader purchases several types of missiles, by which he aims to damage as much value as possible a follower hides into some facilities later. The effectiveness of the missile depends on the type of missile and facility. A payoff of the game is the expected amount of destroyed value. The problem is generalized as a two-person zero-sum game of distributing discrete resources with a leader and a follower. Our problem is to derive a Stackelberg equilibrium for the game. This type of game has an abundance of applications. The problem is first formulated into an integer programming problem with a non-separable objective function of variables and it is further equivalently transformed into a maximin integer knapsack problem. We propose three exacts methods and an approximation method for an optimal solution.     

Two-Stage Stochastic Variational Inequality Arising from Stochastic Programming

We consider a two-stage stochastic variational inequality arising from a general convex two-stage stochastic programming problem, where the random variables have continuous distributions. The equivalence between the two problems is shown under some moderate conditions, and the monotonicity of the two-stage stochastic variational inequality is discussed under additional conditions. We provide a discretization scheme with convergence results and employ the progressive hedging method with double parameterization to solve the discretized stochastic variational inequality. As an application, we show how the water resources management problem under uncertainty can be transformed from a two-stage stochastic programming problem to a two-stage stochastic variational inequality, and how to solve it, using the discretization scheme and the progressive hedging method with double parameterization.

     

Multi-resource shop scheduling with resource flexibility

The shop scheduling problem tackled in this paper integrates many features that can be found in practical settings. Every operation may need several resources to be performed, and furthermore, a resource may be selected in a given set of candidates resources. Finally, we also consider that an operation may have more than one predecessor and/or more than one successor on the routing. The problem is then to both assign operations to resources and sequence operations on the resources, in order to minimize the maximum completion time. A disjunctive graph representation of this problem is presented and a connected neighborhood structure is proposed. The latter can be used to derive a local search algorithm such as tabu search. Finally, some numerical experiments are presented and discussed.     

Resource-based strategies and problem structuring: using resource maps to manage resource systems

The resource-based view of strategy seeks to explain why some firms consistently outperform rivals in the same industry by acquiring a unique set of strategic assets (or resources). However, differences between dominant managerial mental models in management teams lead to disagreement at the moment of implementing distinct resource-building strategies. This managerial and cognitive view of strategic decision making and competition lends itself to investigation through problem structuring methods. We suggest that resource maps, as a problem structuring method, can be used to interpret managerial mental models for strategic decision making in terms of resource-building processes. Through resource maps, we represent the system of asset stocks believed to be most important for driving business performance. We illustrate the framework by comparing and contrasting maps of the system of resources (asset stocks) that best characterize two leading firms in the UK commercial radio broadcasting industry.