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Decision-making Paradox
The decision-making paradox is a phenomenon related to decision-making and the quest for determining reliable decision-making methods. It was first described by Triantaphyllou , and has been recognized in the related literature as a fundamental paradox in multi-criteria decision analysis (MCDA), multi-criteria decision making (MCDM) and decision analysis since then. Description The decision-making paradox was first described in 1989, and further elaborated in the 2000 book by Triantaphyllou on multi-criteria decision analysis (MCDA) / multi-criteria decision making (MCDM). It arises from the observation that different decision-making methods, both normative and descriptive, yield different results, when fed with exactly the same decision problem and data. It has been recognized in the related literature as a fundamental paradox in multi-criteria decision analysis (MCDA) / multi-criteria decision making (MCDM), and decision analysis since then. In a study reported in ''Interna ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Decision-making
In psychology, decision-making (also spelled decision making and decisionmaking) is regarded as the cognitive process resulting in the selection of a belief or a course of action among several possible alternative options. It could be either rational or irrational. The decision-making process is a reasoning process based on assumptions of values, preferences and beliefs of the decision-maker. Every decision-making process produces a final choice, which may or may not prompt action. Research about decision-making is also published under the label problem solving, particularly in European psychological research. Overview Decision-making can be regarded as a problem-solving activity yielding a solution deemed to be optimal, or at least satisfactory. It is therefore a process which can be more or less rational or irrational and can be based on explicit or tacit knowledge and beliefs. Tacit knowledge is often used to fill the gaps in complex decision-making processes. Usuall ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
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Value Analysis
Value engineering (VE) is a systematic analysis of the functions of various components and materials to lower the cost of goods, products and services with a tolerable loss of performance or functionality. Value, as defined, is the ratio of function to cost. Value can therefore be manipulated by either improving the function or reducing the cost. It is a primary tenet of value engineering that basic functions be preserved and not be reduced as a consequence of pursuing value improvements. The term "value management" is sometimes used as a synonym of "value engineering", and both promote the planning and delivery of projects with improved performance The reasoning behind value engineering is as follows: if marketers expect a product to become practically or stylistically obsolete within a specific length of time, they can design it to only last for that specific lifetime. The products could be built with higher-grade components, but with value engineering they ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Superiority And Inferiority Ranking Method
The superiority and inferiority ranking method (or SIR method) is a multi-criteria decision making model (MCDA) which can handle real data and provides six different preference structures for the system user. MCDM is a sub-discipline of operations research that explicitly evaluates multiple conflicting criteria in decision making, both in daily life and in settings such as business, government and medicine. Description It also incorporates outranking rationale to deal with the 'poor' true-criteria preference structure which appears in selecting proper equipment. The superiority and inferiority scores are produced through the generalized criteria. The SIR method can also analyze different criteria without compiling them into a small scale as GAs. See also * Architecture tradeoff analysis method * Decision-making * Decision-making software * Decision-making paradox * Decisional balance sheet * Multicriteria classification problems * Probability distribution In probability ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Grey Relational Analysis
Grey relational analysis (GRA) was developed by Deng Julong of Huazhong University of Science and Technology. It is one of the most widely used models of grey system theory. GRA uses a specific concept of information. It defines situations with no information as black, and those with perfect information as white. However, neither of these idealized situations ever occurs in real world problems. In fact, situations between these extremes, which contain partial information, are described as being grey, hazy or fuzzy. A variant of GRA model, Taguchi-based GRA model, is a popular optimization method in manufacturing engineering. Definition Let X_0=\left(x_0\left(1\right),x_0\left(2\right),\dots ,x_0\left(n\right)\right) is an ideal data set andX_k=\left(x_k\left(1\right),x_k\left(2\right),\dots ,x_k\left(n\right)\right),k\mathrmm are the alternative data sets of the same length. The Grey Relational Grade (GRG) between the two data sets is given by _=\int^n_ where the Grey Relationa ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Aggregated Indices Randomization Method
In applied mathematics and decision making, the aggregated indices randomization method (AIRM) is a modification of a well-known aggregated indices method, targeting complex objects subjected to multi-criteria estimation under uncertainty. AIRM was first developed by the Russian naval applied mathematician Aleksey Krylov around 1908. The main advantage of AIRM over other variants of aggregated indices methods is its ability to cope with poor-quality input information. It can use non-numeric ( ordinal), non-exact ( interval) and non-complete expert information to solve multi-criteria decision analysis (MCDM) problems. An exact and transparent mathematical foundation can assure the precision and fidelity of AIRM results. Background Ordinary aggregated indices method allows comprehensive estimation of complex (multi-attribute) objects’ quality. Examples of such complex objects (decision alternatives, variants of a choice, etc.) may be found in diverse areas of business, industry, ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Dominance-based Rough Set Approach
The dominance-based rough set approach (DRSA) is an extension of rough set theory for multi-criteria decision analysis (MCDA), introduced by Greco, Matarazzo and Słowiński. Greco, S., Matarazzo, B., Słowiński, R.: Rough sets theory for multi-criteria decision analysis. European Journal of Operational Research, 129, 1 (2001) 1–47 The main change compared to the classical rough sets is the substitution for the indiscernibility relation by a dominance relation, which permits one to deal with inconsistencies typical to consideration of criteria and preference-ordered decision classes. Multicriteria classification (sorting) Multicriteria classification ( sorting) is one of the problems considered within MCDA and can be stated as follows: given a set of objects evaluated by a set of criteria (attributes with preference-order domains), assign these objects to some pre-defined and preference-ordered decision classes, such that each object is assigned to exactly one class. Due ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Multi-attribute Utility
In decision theory, a multi-attribute utility function is used to represent the preferences of an agent over bundles of goods either under conditions of certainty about the results of any potential choice, or under conditions of uncertainty. Preliminaries A person has to decide between two or more options. The decision is based on the ''attributes'' of the options. The simplest case is when there is only one attribute, e.g.: money. It is usually assumed that all people prefer more money to less money; hence, the problem in this case is trivial: select the option that gives you more money. In reality, there are two or more attributes. For example, a person has to select between two employment options: option A gives him $12K per month and 20 days of vacation, while option B gives him $15K per month and only 10 days of vacation. The person has to decide between (12K,20) and (15K,10). Different people may have different preferences. Under certain conditions, a person's preferences c ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Analytic Network Process
The analytic network process (ANP) is a more general form of the analytic hierarchy process (AHP) used in multi-criteria decision analysis. AHP structures a decision problem into a hierarchy with a goal, decision criteria, and alternatives, while the ANP structures it as a network. Both then use a system of pairwise comparisons to measure the weights of the components of the structure, and finally to rank the alternatives in the decision. Hierarchy vs. network In the AHP, each element in the hierarchy is considered to be independent of all the others—the decision criteria are considered to be independent of one another, and the alternatives are considered to be independent of the decision criteria and of each other. But in many real-world cases, there is interdependence among the items and the alternatives. ANP does not require independence among elements, so it can be used as an effective tool in these cases. To illustrate this, consider a simple decision about buying an autom ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Decision Analysis
Decision analysis (DA) is the discipline comprising the philosophy, methodology, and professional practice necessary to address important decisions in a formal manner. Decision analysis includes many procedures, methods, and tools for identifying, clearly representing, and formally assessing important aspects of a decision; for prescribing a recommended course of action by applying the maximum expected-utility axiom to a well-formed representation of the decision; and for translating the formal representation of a decision and its corresponding recommendation into insight for the decision maker, and other corporate and non-corporate stakeholders. History In 1931, mathematical philosopher Frank Ramsey pioneered the idea of subjective probability as a representation of an individual’s beliefs or uncertainties. Then, in the 1940s, mathematician John von Neumann and economist Oskar Morgenstern developed an axiomatic basis for utility theory as a way of expressing an individua ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
