Random Sampling Approach to MCDM

Baum, Sanford; Terry, W. Robert; Parekh, Uday N.

doi:10.1007/978-3-642-45527-8_2

Cited by 3 publications

(1 citation statement)

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“…Several methods for obtaining such a representation were proposed. They utilize cluster analysis (Torn, 1980, Morse, 1980, filtering (Steuer and Harris, 1980) or random sampling (Baum et al, 1981).…”

Section: Overview Of Existing Approachesmentioning

confidence: 99%

DISCRET An Interactive Decision Support System for Discrete Alternatives Multicriteria Problems

Majchrzak

1989

Lecture Notes in Economics and Mathematical Systems

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This paper is one of the series of 11 Working Papers presenting the software for interactive decision support and software tools for developing decision support systems. These products constitute the outcome of the contracted study agreement between the System and Decision Sciences Program at IIASA and several Polish scientific institutions. The theoretical part of these results is presented in the IIASA Working Paper WP-88-071 entitled Theory, Software and Testing Ezamples in Decision Support Systems which contains the theoretical and methodological bacgrounds of the software systems developed within the project. This paper presents the DISCRET system. This system has been designed to solve basic multicriteria choice problems in which a finite set of feasible alternatives is explicitly given and for each alternative the value of all criteria are known. The decision maker is assumed to be rational in the sense that he can accept a Pareto-optimal solution as his final solution of the problem. Such a decision problem is rather simple as long as the number of criteria and alternatives is small. However, if the number of alternatives and/or criteria grows, the human information processing capabilities may reach their limits and therefore decision support facilities need to be utilized to guarantee efficient decision making.

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Section: Overview Of Existing Approachesmentioning

confidence: 99%

DISCRET An Interactive Decision Support System for Discrete Alternatives Multicriteria Problems

Majchrzak

1989

Lecture Notes in Economics and Mathematical Systems

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Supporting decision making in combinatorially explosive multicriteria situations

Purao

Jain

Nazareth

1999

Decision Support Systems

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Generating optimal and near-optimal solutions to facility location problems

Church

Baez

2020

Environment and Planning B: Urban Analytics and City Science

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There is a decided bent toward finding an optimal solution to a given facility location problem instance, even when there may be multiple optima or competitive near-optimal solutions. Identifying alternate solutions is often ignored in model application, even when such solutions may be preferred if they were known to exist. In this paper we discuss why generating close-to-optimal alternatives should be the preferred approach in solving spatial optimization problems, especially when it involves an application. There exists a classic approach for finding all alternate optima. This approach can be easily expanded to identify all near-optimal solutions to any discrete location model. We demonstrate the use of this technique for two classic problems: the p-median problem and the maximal covering location problem. Unfortunately, we have found that it can be mired in computational issues, even when problems are relatively small. We propose a new approach that overcomes some of these computational issues in finding alternate optima and near-optimal solutions.

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Random Sampling Approach to MCDM

Cited by 3 publications

References 8 publications

DISCRET An Interactive Decision Support System for Discrete Alternatives Multicriteria Problems

DISCRET An Interactive Decision Support System for Discrete Alternatives Multicriteria Problems

Supporting decision making in combinatorially explosive multicriteria situations

Generating optimal and near-optimal solutions to facility location problems

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