The bounded interval generalized assignment model

The bounded interval generalized assignment model is a “many-for-one” assignment model. Each task must be assigned to exactly one agent; however, each agent can be assigned multiple tasks as long as the agent resource consumed by performing the assigned tasks falls within a specified interval. The bounded interval generalized assignment model is formulated, and an algorithm for its solution is developed. Algorithms for the bounded interval versions of the semiassignment model and sources-to-uses transportation model are also discussed.     

Cyclic scheduling in robotic flowshops with bounded work‐in‐process levels

This study addresses cyclic scheduling in robotic flowshops with bounded work‐in‐process (WIP) levels. The objective is to minimize the cycle time or, equivalently, to maximize the throughput, under the condition that the WIP level is bounded from above by a given integer number. We present several strongly polynomial algorithms for the 2‐cyclic robotic flowshop scheduling problems for various WIP levels. © 2010 Wiley Periodicals, Inc. Naval Research Logistics 58: 1–16, 2011     

Parametric analysis of linear programs with upper bounded variables

Linear programming problems with upper bounded variables can be solved by regular simplex method by considering upper bounding constraints as explicit constraints of the problem. However, more efficient methods exist which consider these upper bound constraints implicitly. When parametric analysis for problems with upper bounds is to be carried out, one can use the regular parameter analysis by considering the upper bound constraints explicitly. This paper develops formulas for parametric analysis where upper bound constraints are used implicitly, thus reducing the size of the basic matrix.     

Equivalent knapsack-type formulations of bounded integer linear programs: An alternative approach

In this paper we show that every bounded integer linear program can be transformed into an integer program involving one single linear constraint and upper and lower bounds on the variables, such that the solution space of the original problem coincides with that one of the equivalent knapsack-type problem.     

Determining optimal sizes of bounded batches with rejection via quadratic min‐cost flow

In this article, we consider a single machine scheduling problem, in which identical jobs are split into batches of bounded sizes. For each batch, it is allowed to produce less jobs than a given upper bound, that is, some jobs in a batch can be rejected, in which case a penalty is paid for each rejected job. The objective function is the sum of several components, including the sum of the completion times, total delivery cost, and total rejection cost. We reduce this problem to a min‐cost flow problem with a convex quadratic function and adapt Tamir's algorithm for its solution. © 2017 Wiley Periodicals, Inc. Naval Research Logistics 64: 217–224, 2017     

A general treatment of upper unbounded and bounded hitchcock problems

This paper is designed to treat (a) the problem of the determination of the absolute minimum cost, with the associated assignments, when there is no limit, N, on the number of parcels available for shipment in a modified Hitchcock problem. This is accomplished with the use of a transformed cost matrix. C*, to which the so-called transportation paradox does not apply. The general Hitchcock solution using C* gives the cost T*, which is the absolute minimum cost of the original problem, as well as sets of assignments which are readily transformed to give the general assignments of the original problem. The sum of these latter assignments gives the value of N_u, the unbounded N for minimum cost. In addition, this paper is designed to show (b) how the method of reduced matrices may be used, (c) how a particular Hitchcock solution can be used to determine a general solution so that one solution using C* can provide the general answer, (d) how the results may be modified to apply to problems with fixed N, and hence (e) to determine the function of the decreasing T as N approaches N_u, and finally (f) to provide a treatment when the supplies at origin i and/or the demands at destination j, are bounded.     

非线性积分方程的周期解

以（Cg,｜.｜g）为相空间,研究具有无限时滞非线性积分方程周期解的存在性,利用Schauder-Tychonov不动点定理证明方程解的g一致有界性和g一致最终有界性蕴含周期解的存在性。     

Convergence of the bounded fixed charge programming problem

Calculating the solution for a mixed integer linear programming problem has been problematic for any sizable dimension because of the time required. Accordingly, an improved method for the fixed charge problem is presented here. The method is a modification of a bounding technique first suggested by Balinski, and it exploits fully the ratio of costio-use, first described by Cooper and Drebes. It exploits those local properties which have global application so that enumeration is confined to those relatively few combinations which cannot be evaluated otherwise.     

变量有界线性目标规划的对偶算法

本文讨论了变量有界的线性目标规划问题,给出了求解这类问题的一个对偶算法,此方法与变量有界线性规划问题的对偶算法相类似。文中证明了算法的有效性,并举例说明了计算过程。     

提供有界延迟服务的网络结构

将来的计算机网络必须支持具有不同通信量和不同服务质量（ＱｏＳ）要求的应用，有界延迟服务保证所有应用包的延迟都不超过给定延迟上界。本文首先提出有界延迟实时服务网络的框架，详细说明了其关键部件的功能和工作原理，并阐述了分析它们性能的技术，最后讨论了设计有界延迟服务网络在性能与实现复杂性之间的折衷。     

一种系统存在有界干扰的混合自适应极点配置方案

主要讨论了确定性单输入单输出连续时间系统存在有界干扰时的混合自适应极点配置问题,给出了一种间接式混合自适应极点配置方案,并以某飞行器自动驾驶仪为例,对该方案进行了数字仿真,结果表明,该方案能有效地抑制有界干扰的不利影响。     

基于有限理性理论的虚拟士兵感知行为建模研究

针对当前虚拟士兵感知行为模型的缺陷,介绍有限理性理论和基于有限理性虚拟士兵的概念,分析了加入有限理性理论的虚拟士兵的特点,提出了基于有限理性虚拟士兵的感知行为模型。该模型包括有限视觉模型、有限听觉模型和有限记忆模型,基于该感知模型的虚拟士兵在感知、决策和运动能力方面与类似真实士兵具有较高的一致性。这对虚拟士兵的感知行为建模研究具有一定的探索意义。     

最大避障圆问题的提出与初探

提出了一个在有界区域内求对已知各障碍物的最大避障圆问题。首先给出此问题的数学描述,然后分析了当有界区域为圆域,并将各障碍物看成一个有限点集时,避障圆的基本性质,从而得到一种求最大避障圆的有效算法。     

Techniques for establishing ergodic and recurrence properties of continuous-valued markov chains

We present techniques for classifying Markov chains with a continuous state space as either ergodic or recurrent. These methods are analogous to those of Foster for countable space chains. The theory is presented in the first half of the paper, while the second half consists of examples illustrating these techniques. The technique for proving ergodicity involves, in practice, three steps: showing that the chain is irreducible in a suitable sense; verifying that the mean hitting times on certain (usually bounded) sets are bounded, by using a “mean drift” criterion analogous to that of Foster; and finally, checking that the chain is such that bounded mean hitting times for these sets does actually imply ergodicity. The examples comprise a number of known and new results: using our techniques we investigate random walks, queues with waiting-time-dependent service times, dams with general and random-release rules, the s-S inventory model, and feedback models.     

Price and capacity decisions of service systems with boundedly rational customers

We consider price and capacity decisions for a profit‐maximizing service provider in a single server queueing system, in which customers are boundedly rational and decide whether to join the service according to a multinomial logit model. We find two potential price‐capacity pair solutions for the first‐order condition of the profit‐maximizing problem. Profit is maximized at the solution with a larger capacity, but minimized at the smaller one. We then consider a dynamically adjusting capacity system to mimic a real‐life situation and find that the maximum can be reached only when the initial service rate is larger than a certain threshold; otherwise, the system capacity and demand shrink to zero. We also find that a higher level of customers’ bounded rationality does not necessarily benefit a firm, nor does it necessarily allow service to be sustained. We extend our analysis to a setting in which customers’ bounded rationality level is related to historical demand and find that such a setting makes service easier to sustain. Finally we find that bounded rationality always harms social welfare.     

Multiple-attribute decision making with partial information: The expected-value criterion

We consider the multiple-attribute decision problem with finite action set and additive utility function. We suppose that the decision maker cannot specify nonnegative weights for the various attributes which would resolve the problem, but that he/she supplies ordinal information about these weights which can be translated into a set of linear constraints restricting their values. A bounded polytope W of feasible weight vectors is thus determined. Supposing that each element of W has the same chance of being the “appropriate one,” we compute the expected utility value of each action. The computation method uses a combination of numerical integration and Monte Carlo simulation and is equivalent to finding the center of mass of the bounded polytope W . Comparisons are made with another criterion already presented, the comparative hyper-volume criterion, and two small examples are presented.     

关于U算子有界性的证明

利用Hardy Littlewood极大算子及性质与分数次极大算子及性质 ,证明了u(x)在Lq(Rn) ,L∝ ,Lq(E)空间上是有界的 ,Coσoπeβ定理应予以推广。     

有容量限制的运输问题

具有容量限制的运输问题可以用有界变量的线性规划问题求解,但是问题的规模往往变得很大,给求解带来不便。本文给出求解这一问题的表上作业法。