Optimal Stopping and Gittins' Indices for Piecewise Deterministic Evolution Processes

Westudy the optimal stopping problem for a class of continuoustime random evolutions described by stochastic differential equationswith alternating renewal processes as noise sources. The exactsolution of this stopping problem provides, in explicit form,an expression for the Gittins' indices needed to derive the optimalscheduling of a class of multi-armed bandit problems in continuoustime. The underlying random processes to which the bandits' armsobey are random velocity models. Such processes are commonlyused to describe, in the fluid limit, the random production flowsdelivered by failure prone machines.     

Implementation Strategies for First-Class Continuations

Scheme and Smalltalk continuations may have unlimited extent. This means that a purely stack-based implementation of continuations, as suffices for most languages, is inadequate. We review several implementation strategies for continuations and compare their performance using instruction counts for the normal case and continuation-intensive synthetic benchmarks for other scenarios, including coroutines and multitasking. All of the strategies constrain a compiler in some way, resulting in indirect costs that are hard to measure directly. We use related measurements on a set of benchmarks to calculate upper bounds for these indirect costs.     

BIAS CALCULATIONS FOR ADAPTIVE URN DESIGNS

A clinical trial model is considered in which two treatments with immediate binary responses are to be compared. An adaptive urn design is used to assign patients to the treatments. The bias and variance of the maximum likelihood estimators of the probabilities of success are derived by differentiating the fundamental identity of sequential analysis. By embedding the design in a continuous-time process, probability generating functions are then calculated to obtain approximations for the bias and variance. Simulation is used to assess the accuracy of the approximations. It is shown that the bias cannot be ignored, and that the adaptive rules which are subcritical in nature have the most mathematically tractable bias and are the least variable. Methods for correcting for the bias are also addressed.     

Study of Optimal Adaptive Rule in Testing Composite Hypothesis

Abstract

In this article on sequential adaptive testing, we have studied the optimal allocation between two populations for testing a composite hypothesis involving the parameters, with the goal of decreasing allocation of one of the treatments to the order of the logarithm of the sample size while decreasing the probability of incorrect selection to zero. We have proved the result for large sample sizes both mathematically and by simulation studies.     

Optimal allocation for estimating the mean of a bivariate polynomial

Suppose we wish to estimate the mean of some polynomial function of random variables from two independent Bernoulli populations, the parameters of which. rhemselves, are modeled as independent beta random variables. It. is assumed that the t.otal sample size for the experiment is fixed, but that the number of experimental units observed from each population may be random. This problem arises, ior example, when estimating the fault tolerance of a system by testing its compomentc individually. Using a decision theorebic approach, we seek to minimize the Bayes risk that arises from using a squared error loss function The Bayes estimator can lw detrmined in a straightforwardmanner, so the problem of optimal estimation rcduces. therefore, to a problem of optimallocatton of the samples between the two populatiorls. This can be solved via dynamic programming. Similar programming techniques are utilized to evaluate properties of a number of ad hoc allocation strategies that might also be collsidered for use in this problem.Two sample polynomials are analyzed along with a number of examples indicating the effects of different prior parameter settings. The effects of differences between prior pararueters used in the design and analysis stages of the experiment are also examined. For the polynomials considered, the adaptive strategies are found to be especially robust. We discuss computational techniques that facilitate such analyses by permitting rapid re-evaluation of strategies. Capabilities of this sort enrouragepeople to explorr designs more fully and to consider them from a number of different viewpuillts.     

两阶段补偿式跨流域调水配置算法及应用

本文将跨流域调水工程进行概化处理以分析本地水资源和从外调入水(简称外调水)之间的联合调配方式.针对两部制水价运行管理机制,提出符合实际管理需求的两阶段补偿式外调水配置算法,实现本地水和外调水的联合配置.算法中第1阶段进行外调水优先利用量的配置,第2阶段在本地水供水后对外调水进行补偿配置,可以实现满足总体分水原则下的外调水合理配置过程.采用该算法对规划水平年下的海河流域在南水北调工程实施后的配置进行了分析,并模拟了不同策略下的调水分配方案.     

资源配置政策影响下的大学组织趋同现象分析

资源配置政策极大地影响着高等教育的发展,同时也塑造着大学组织的行为。而政府往往通过倾斜性的资源配置政策,扶持少量大学成为办学榜样,诱导其他大学模仿而形成组织趋同。为了避免大学组织过度趋同,政府应对原有的资源配置方式进行适当调整,引导各类各层次大学个性化办学。     

Need and design of short-term auctions in the EU gas markets

In the EU, gas markets are based on socializing network flexibility services. However, shippers have different preferences on network flexibility, which are not reflected in current allocation models. We propose the introduction of auction mechanisms to allocate network services in the short run. The auction aims to represent simultaneously the diversity of players′ preferences and the trade-offs implied by network constraints. Two sealed-bid auctions are proposed: (a) an auction based on bids for gas, which allocates network services through the minimization of gas price differences; (b) an auction with explicit bids for line-pack, which allows shippers′ valuation of line-pack storage.     

A heuristic approach for resource constrained project scheduling with uncertain activity durations

In this paper, we address the resource constrained project scheduling problem with uncertain activity durations. Project activities are assumed to have known deterministic renewable resource requirements and uncertain durations, described by independent random variables with a known probability distribution function. To tackle the problem solution we propose a heuristic method which relies on a stage wise decomposition of the problem and on the use of joint probabilistic constraints.     

市场经济中的城市规划

市场经济中的城市规划应该放弃传统的那种按照理想方式为城市量体裁衣的简单作法 ,而要以实现城市空间与经济发展的动态适应为高层次目标。虽同为资源配置手段 ,战略层面的规划任务主要是维护城市发展的外部效益 ,在此前提下 ,实施层面的规划则应充分满足微观行为的内部经济性要求