Multiple Objective Decision Making - Methods and Applications
Hwang, Ching-Lai; Masud, Abu Syed Md
ISBN 10: 3540091114 ISBN 13: 9783540091110
Published by Springer-Verlag Berlin and Heidelberg GmbH & Co. KG, 1979
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Series: Lecture Notes in Economics and Mathematical Systems. Num Pages: 370 pages, biography. BIC Classification: KCA; KJT. Category: (P) Professional & Vocational. Dimension: 244 x 170 x 19. Weight in Grams: 640. . 1979. Paperback. . . . . Seller Inventory # V9783540091110
Synopsis:
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.
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Title: Multiple Objective Decision Making - Methods...
Publisher: Springer-Verlag Berlin and Heidelberg GmbH & Co. KG
Publication Date: 1979
Binding: Soft cover
Condition: New
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Multiple Objective Decision Making. - Methods and Applications. A State-of-the-Art Survey. (= Lecture Notes in Economics and Mathematical Systems, Band 164)
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ISBN 10: 3540091114
ISBN 13: 9783540091110
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Multiple Objective Decision Making - Methods and Applications (Lecture Notes in Economics and Mathematical Systems) (Volume 164)
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Condition: Poor. Volume 164. This is an ex-library book and may have the usual library/used-book markings inside.This book has soft covers. In poor condition, suitable as a reading copy. Please note the Image in this listing is a stock photo and may not match the covers of the actual item,750grams, ISBN:3540091114. Seller Inventory # 7087993
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Multiple Objective Decision Making - Methods and Applications: A State-of-the-Art Survey (Lecture Notes in Economics and Mathematical Systems)
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Multiple Objective Decision Making - Methods and Applications: A State-of-the-Art Survey (Lecture Notes in Economics and Mathematical Systems)
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Multiple Objective Decision Making - Methods and Applications
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Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. 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 ma. Seller Inventory # 4880338
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Multiple Objective Decision Making ? Methods and Applications: A State-of-the-Art Survey (Lecture Notes in Economics and Mathematical Systems, 164)
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Multiple Objective Decision Making Ù Methods and Applications : A Stateoftheart Survey
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Multiple Objective Decision Making - Methods and Applications
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Springer Berlin Heidelberg, Springer Berlin Heidelberg Feb 1979, 1979
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Taschenbuch. Condition: Neu. Neuware -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.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 372 pp. Englisch. Seller Inventory # 9783540091110
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Multiple Objective Decision Making ¿ Methods and Applications : A State-of-the-Art Survey
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Springer Berlin Heidelberg, 1979
ISBN 10: 3540091114
ISBN 13: 9783540091110
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Taschenbuch. Condition: Neu. Druck auf Anfrage Neuware - Printed after ordering - 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. Seller Inventory # 9783540091110
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Multiple Objective Decision Making ¿ Methods and Applications
Published by
Springer Berlin Heidelberg Feb 1979, 1979
ISBN 10: 3540091114
ISBN 13: 9783540091110
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Taschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -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. 372 pp. Englisch. Seller Inventory # 9783540091110
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