Multiple Decision Procedures

Multiple Decision Procedures PDF Author: Shanti S. Gupta
Publisher: SIAM
ISBN: 0898715326
Category : Mathematics
Languages : en
Pages : 592

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Book Description
An encyclopaedic coverage of the literature in the area of ranking and selection procedures. It also deals with the estimation of unknown ordered parameters. This book can serve as a text for a graduate topics course in ranking and selection. It is also a valuable reference for researchers and practitioners.

Multiple Decision Procedures

Multiple Decision Procedures PDF Author: Shanti S. Gupta
Publisher: SIAM
ISBN: 0898715326
Category : Mathematics
Languages : en
Pages : 592

Get Book

Book Description
An encyclopaedic coverage of the literature in the area of ranking and selection procedures. It also deals with the estimation of unknown ordered parameters. This book can serve as a text for a graduate topics course in ranking and selection. It is also a valuable reference for researchers and practitioners.

Multiple Decision Procedures for Ranking Means of Normal Populations

Multiple Decision Procedures for Ranking Means of Normal Populations PDF Author: R. E. Bechhoefer
Publisher:
ISBN:
Category : Decision making
Languages : en
Pages : 40

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Book Description


Multiple Decision Procedures for Ranking Means

Multiple Decision Procedures for Ranking Means PDF Author: R. E. Bechhoefer
Publisher:
ISBN:
Category : Population
Languages : en
Pages : 10

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Book Description


Multiple Decision Procedures for ANOVA of Two-level Factorial Fixed-effects Replication-free Experiments

Multiple Decision Procedures for ANOVA of Two-level Factorial Fixed-effects Replication-free Experiments PDF Author: Arthur G. Holms
Publisher:
ISBN:
Category : Factorial experiment designs
Languages : en
Pages : 58

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Book Description


A Sequential Multiple Decision Procedure for Selecting the Best One of Several Normal Populations with a Common Unknown Variance, and Its Use with Various Experimental Designs

A Sequential Multiple Decision Procedure for Selecting the Best One of Several Normal Populations with a Common Unknown Variance, and Its Use with Various Experimental Designs PDF Author: R. E. Bechhoefer
Publisher:
ISBN:
Category : Experimental design
Languages : en
Pages : 46

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Book Description


Decision Procedures

Decision Procedures PDF Author: Daniel Kroening
Publisher: Springer
ISBN: 3662504979
Category : Computers
Languages : en
Pages : 356

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Book Description
A decision procedure is an algorithm that, given a decision problem, terminates with a correct yes/no answer. Here, the authors focus on theories that are expressive enough to model real problems, but are still decidable. Specifically, the book concentrates on decision procedures for first-order theories that are commonly used in automated verification and reasoning, theorem-proving, compiler optimization and operations research. The techniques described in the book draw from fields such as graph theory and logic, and are routinely used in industry. The authors introduce the basic terminology of satisfiability modulo theories and then, in separate chapters, study decision procedures for each of the following theories: propositional logic; equalities and uninterpreted functions; linear arithmetic; bit vectors; arrays; pointer logic; and quantified formulas.

A Single-sample Multiple-decision Procedure for Selecting the Multinomial Event which Has the Highest Probability

A Single-sample Multiple-decision Procedure for Selecting the Multinomial Event which Has the Highest Probability PDF Author: Robert Eric Bechhofer
Publisher:
ISBN:
Category : Probabilities
Languages : en
Pages : 58

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Book Description
The problem of selecting the multinomial event which has the highest probability is formulated as a multiple-decision selection problem. Before experimentation starts the experimenter must specify two constants ([theta]*, P*) which are incorporated into the requirement: "The probability of a correct selection is to be equal to or greater than P* whenever the true (but unknown) ratio of the largest to the second largest of the poplation probabilities is equal to or greater than [theta]*." A single-sample procedure which meets the requirement is proposed. The heart of the procedure is the proper choice of N, the number of trials. Two methods of determining N are described: the first is exact and is to be used when N is small; the second is approximate and is to be used when N is large. Tables and sample calculations are provided.

A Sequential Multiple-decision Procedure for Selecting the Best One of Several Normal Populations with a Common Unknown Variance. Ii. Monte Carlo Sampling Results and New Computing Formulae

A Sequential Multiple-decision Procedure for Selecting the Best One of Several Normal Populations with a Common Unknown Variance. Ii. Monte Carlo Sampling Results and New Computing Formulae PDF Author: Robert Eric Bechhofer
Publisher:
ISBN:
Category : Monte Carlo method
Languages : en
Pages : 62

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Book Description
Contents: Statement of the statistical problem S atistical assumptions The experimenter's goal, specification, and requirement Procedure D and the new computing formulae Description of Procedure D Definition of symbols The sampling, stopping, and terminal de cision rules Computation of the stopping statistic Use of Procedure D (method B) with various experimental designs Simplified computing formulae Numerical example Monte Carlo sampling results with Procedure D Description of the sampling procedure Sampling results Discussion of sampling results.

Multiple Objective Decision Making — Methods and Applications

Multiple Objective Decision Making — Methods and Applications PDF Author: C.-L. Hwang
Publisher: Springer Science & Business Media
ISBN: 3642455115
Category : Business & Economics
Languages : en
Pages : 366

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Book Description
Decision making is the process of selecting a possible course of action from all the available alternatives. In almost all such problems the multiplicity of criteria for judging the alternatives is pervasive. That is, for many such problems, the decision maker (OM) wants to attain more than one objective or goal in selecting the course of action while satisfying the constraints dictated by environment, processes, and resources. Another characteristic of these problems is that the objectives are apparently non commensurable. Mathematically, these problems can be represented as: (1. 1 ) subject to: gi(~) ~ 0, ,', . . . ,. ! where ~ is an n dimensional decision variable vector. The problem consists of n decision variables, m constraints and k objectives. Any or all of the functions may be nonlinear. In literature this problem is often referred to as a vector maximum problem (VMP). Traditionally there are two approaches for solving the VMP. One of them is to optimize one of the objectives while appending the other objectives to a constraint set so that the optimal solution would satisfy these objectives at least up to a predetermined level. The problem is given as: Max f. ~) 1 (1. 2) subject to: where at is any acceptable predetermined level for objective t. The other approach is to optimize a super-objective function created by multiplying each 2 objective function with a suitable weight and then by adding them together.

Multiple Attribute Decision Making

Multiple Attribute Decision Making PDF Author: Ching-Lai Hwang
Publisher: Springer Science & Business Media
ISBN: 3642483186
Category : Business & Economics
Languages : en
Pages : 274

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Book Description
This mono graph is intended for an advanced undergraduate or graduate course as weIl as for the researchers who want a compilation of developments in this rapidly growing field of operations research. This is a sequel to our previous work entitled "Multiple Objective Decision Making--Methods and Applications: A State-of-the-Art Survey," (No. 164 of the Lecture Notes). The literature on methods and applications of Multiple Attribute Decision Making (MADM) has been reviewed and classified systematically. This study provides readers with a capsule look into the existing methods, their char acteristics, and applicability to analysis of MADM problems. The basic MADM concepts are defined and a standard notation is introduced in Part 11. Also introduced are foundations such as models for MADM, trans formation of attributes, fuzzy decision rules, and methods for assessing weight. A system of classifying seventeen major MADM methods is presented. These methods have been proposed by researchers in diversified disciplines; half of them are classical ones, but the other half have appeared recently. The basic concept, the computational procedure, and the characteristics of each of these methods are presented concisely in Part 111. The computational procedure of each method is illustrated by solving a simple numerical example. Part IV of the survey deals with the applications of these MADM methods.