Sharp and simple bounds for the Erlang delay and loss formulae

We prove some simple and sharp lower and upper bounds for the Erlang delay and loss formulae and for the number of servers that invert the Erlang delay and loss formulae. We also suggest simple and sharp approximations for the number of servers that invert the Erlang delay and loss formulae. We illustrate the importance of these bounds by using them to establish convexity proofs. We show that the probability that the M/M/s queue is empty is a decreasing and convex function of the traffic intensity. We also give a very short proof to show that the Erlang delay formula is convex in the traffic intensity when the number of servers is held constant. The complete proof of this classical result has never been published. We also give a very short proof to show that the Erlang delay formula is a convex function of the (positive integer) number of servers. One of our results is then used to get a sharp bound to the Flow Assignment Problem.     

Tight lower bound on the probability of a binomial exceeding its expectation

We give the proof of a tight lower bound on the probability that a binomial random variable exceeds its expected value. The inequality plays an important role in a variety of contexts, including the analysis of relative deviation bounds in learning theory and generalization bounds for unbounded loss functions.     

Super-fast validated solution of linear systems

Validated solution of a problem means to compute error bounds for a solution in finite precision. This includes the proof of existence of a solution. The computed error bounds are to be correct including all possible effects of rounding errors. The fastest known validation algorithm for the solution of a system of linear equations requires twice the computing time of a standard (purely) numerical algorithm. In this paper we present a super-fast validation algorithm for linear systems with symmetric positive definite matrix. This means that the entire computing time for the validation algorithm including computation of an approximated solution is the same as for a standard numerical algorithm. Numerical results are presented.     

Dahlquist's first barrier for multistage multistep formulas

Dahlquist's proof of his barrier for the order of stable linear multistep methods is combined with Reimer's proof of the corresponding barrier for multistep multiderivative methods. This leads to a shortening of Reimer's original proof and gives lower bounds for the error constant. These bounds are then studied for high error order and are used to model the optimal order and stepsize selection in an idealized integration code. Dedicated to Professor Germund Dahlquist on the occasion of his sixtieth birthday.     

Integral means of analytic functions

Sharp bounds for general integral means of analytic functions in the unit disc are determined. These bounds depend only on the moduli of the points on the boundary of the image domain nearest to and farthest from the origin. The proof is shown to be a simple application of a deep theorem of A. Beurling in potential theory.     

The static bicycle relocation problem with demand intervals

This study introduces the Static Bicycle Relocation Problem with Demand Intervals (SBRP-DI), a variant of the One Commodity Pickup and Delivery Traveling Salesman Problem (1-PDTSP). In the SBRP-DI, the stations are required to have an inventory of bicycles lying between given lower and upper bounds and initially have an inventory which does not necessarily lie between these bounds. The problem consists of redistributing the bicycles among the stations, using a single capacitated vehicle, so that the bounding constraints are satisfied and the repositioning cost is minimized. The real-world application of this problem arises in rebalancing operations for shared bicycle systems. The repositioning subproblem associated with a fixed route is shown to be a minimum cost network problem, even in the presence of handling costs. An integer programming formulation for the SBRP-DI are presented, together with valid inequalities adapted from constraints derived in the context of other routing problems and a Benders decomposition scheme. Computational results for instances adapted from the 1-PDTSP are provided for two branch-and-cut algorithms, the first one for the full formulation, and the second one with the Benders decomposition.     

The influence of sequential extremal processes on the partial sum process

In this paper we derive general upper bounds for the total variation distance between the distributions of a partial sum process in row-wise independent, non-negative triangular arrays and the sum of a fixed number of corresponding extremal processes. As a special case we receive bounds for the supremum distance between the distribution functions of a partial sum and the sum of corresponding upper extremes which improve upon existing results. The outcome may be interpreted as the influence of large insurance claims on the total loss. Moreover, under an additional infinitesimal condition we also prove explicit bounds for limits of the above quantities. Thereby we give a didactic and elementary proof of the Ferguson–Klass representation of Lévy processes on ?_?≥?0 which reflects the influence of extremal processes in insurance.     

Sturm bounds for Siegel modular forms of degree 2 and odd weights

Mathematische Zeitschrift - We correct the proof of the theorem in the previous paper presented by Kikuta, which concerns Sturm bounds for Siegel modular forms of degree 2 and of even weights...     

Complexity lower bounds for machine computing models

The article is the text of a survey report on methods of obtaining lower bounds on the computational complexity for abstract computers. Besides the methods for obtaining the lower bounds, related methods for the simulation of some machines by others, with the preservation of some complexity measures at the expense of increase in others (trade-off results), are presented. Methods of crossing sequences, tails, overlaps, and related methods are examined. A new proof of an old result is sometimes given to illustrate the working of a method, or a new result is proved.Translated from Zapiski Nauchnykh Seminarov Leningradskogo Otdeleniya Matematicheskogo Instituta im. V. A. Steklova AN SSSR, Vol. 118, pp. 4–24, 1982.     

Simple Product-Form Bounds for Queueing Networks with Finite Clusters

Queueing networks are studied with finite capacities for clusters of stations, rather than for individual stations. First, an instructive tandem cluster example is studied to show that a product-form modification method for networks with finite stations can be extended to networks with finite clusters. Next, general results are established by which finite clusters can be regarded as finite aggregate stations. By these results product-form modifications for finite stations can be extended to product-form modifications for finite clusters by just considering a network at cluster level. This may lead to simple performance bounds. A number of illustrative examples with numerical support are provided.     

Proof complexity of propositional default logic

Default logic is one of the most popular and successful formalisms for non-monotonic reasoning. In 2002, Bonatti and Olivetti introduced several sequent calculi for credulous and skeptical reasoning in propositional default logic. In this paper we examine these calculi from a proof-complexity perspective. In particular, we show that the calculus for credulous reasoning obeys almost the same bounds on the proof size as Gentzen??s system LK. Hence proving lower bounds for credulous reasoning will be as hard as proving lower bounds for LK. On the other hand, we show an exponential lower bound to the proof size in Bonatti and Olivetti??s enhanced calculus for skeptical default reasoning.     

On the convexity for the expected total cost per unit time of the EPQ model with scrap,rework and stochastic machine breakdown

This study explores the economic production quantity model with scrap, rework and stochastic machine breakdown. The main purpose of this paper is twofold:(P1) This paper will adopt the rigorous methods of mathematics to demonstrate that the expected total cost per unit time is convex on all positive numbers to improve the conditional convexity in Theorem 1 of Chiu et al. (2010) [7].(P2) This paper gives the concrete proof to provide bounds for the optimal production run time to remove the logical shortcomings of mathematics presented in proof of Theorem 2 of Chiu et al. (2010) [7].     

双线性非协调有限元逼近的梯度恢复后验误差估计

给出了二阶椭圆方程的双线性非协调有限元逼近的梯度恢复后验误差估计.该误差估计是在Q_1非协调元上得到的,并给出了误差的上下界.进一步证明该误差估计在拟一致网格上是渐进精确地.证明依赖于clement插值和Helmholtz分解,数值结果验证了理论的正确性.     

Square function and heat flow estimates on domains

The first purpose of this note is to provide a proof of the usual square function estimate on L^p(Ω). It turns out to follow directly from a generic Mikhlin multiplier theorem obtained by Alexopoulos, and we provide a sketch of its proof in the Appendix for the reader’s convenience. We also relate such bounds to a weaker version of the square function estimate which is enough in most instances involving dispersive PDEs and relies on Gaussian bounds on the heat kernel (such bounds are the key to Alexopoulos’result as well). Moreover, we obtain several useful L^p(Ω;H) bounds for (the derivatives of) the heat flow with values in a given Hilbert space H.     

An Adaptive Neural Network Model for Nonlinear Programming Problems

In this paper a canonical neural network with adaptively changing synaptic weights and activation function parameters is presented to solve general nonlinear programming problems. The basic part of the model is a sub-network used to find a solution of quadratic programming problems with simple upper and lower bounds. By sequentially activating the sub-network under the control of an external computer or a special analog or digital processor that adjusts the weights and parameters, one then solves general nonlinear programming problems. Convergence proof and numerical results are given.     

A Theoretical Model for Particulate Transport from an Elevated Source in the Atmosphere

An analytical model for the transport of dust released froman elevated source into the atmosphere is presented. This treatmentincorporates horizontal advection with the airflow past thesource, vertical settling under gravity and dispersion due toatmospheric turbulence. Mathematical features include the derivationof a fairly simple solution, expressed in terms of well-knownfunctions. Expressions for the maximum ground level concentrationof dust are given in terms of the particle density and size.It is suggested that the validity of these upper bounds couldbe tested by field surveys around power stations.     

New Linear Program Performance Bounds for Queueing Networks

We obtain new linear programs for bounding the performance and proving the stability of queueing networks. They exploit the key facts that the transition probabilities of queueing networks are shift invariant on the relative interiors of faces and the cost functions of interest are linear in the state. A systematic procedure for choosing different quadratic functions on the relative interiors of faces to serve as surrogates of the differential costs in an inequality relaxation of the average cost function leads to linear program bounds. These bounds are probably better than earlier known bounds. It is also shown how to incorporate additional features, such as the presence of virtual multi-server stations to further improve the bounds. The approach also extends to provide functional bounds valid for all arrival rates.     

Comparisons of weak regular splittings and multisplitting methods

Summary Comparison results for weak regular splittings of monotone matrices are derived. As an application we get upper and lower bounds for the convergence rate of iterative procedures based on multisplittings. This yields a very simple proof of results of Neumann-Plemmons on upper bounds, and establishes lower bounds, which has in special cases been conjectured by these authors.Dedicated to the memory of Peter Henrici     

Two-sided estimates for essential height in Shirshov’s Height Theorem

The paper is focused on two-sided estimates for the essential height in Shirshov??s Height Theorem. The concepts of the selective height and strong n-divisibility directly related to the height and n-divisibility are introduced. We prove lower and upper bounds for the selective height over nonstrongly n-divisible words of length 2. For any n and sufficiently large l these bounds differ at most twice. The case of words of length 3 is also studied. The case of words of length 2 can be generalized to the proof of an upper exponential estimate in Shirshov??s Height Theorem. The proof uses the idea of V.N. Latyshev related to the application of Dilworth??s theorem to the study of non n-divisible words.     

TRUST REGION METHOD IN NEURAL NETWORK

1.IntroductionHopfieldandTank[5]presentedamodeltosolvetravellingsalesmanproblem,thusinitiatingtheapplicationofneuralnetwork(NN)inthefieldofoptimization.SincethenmanyNNmodelshavebeenproposedtosolvelinearprogramming(LP)problems(13,8,11,14,15])andquadraticprogramming(oP)problems([1,8,20]),asLPandoPhavefundamentalimportanceinthetheoryandpracticeofoptimization.Therewerealsoafewmodelsforgeneralnonlinearprogramming(NP)problem([2,6,9,18]).InthispaperwewillpresentaHopfield-typeneuralnetworkmodelw…