Skip to main content
Fachgebiete
Automobil + Motoren Bauwesen + Immobilien Business IT + Informatik Elektrotechnik + Elektronik Energie + Nachhaltigkeit Finance + Banking Management + Führung Marketing + Vertrieb Maschinenbau + Werkstoffe Versicherung + Risiko
DE
EN
Themenseiten
Organisationspsychologie Projektmanagement Marketing Smart Manufacturing
Bücher
Zeitschriften
Weitere Formate
Podcasts Webinare Technik Webinare Wirtschaft Kongresse Veranstaltungskalender Awards
Jetzt Einzelzugang starten
Zugang für Unternehmen
Referenzkunden
ATZ-Fachkongress

Chassis.tech plus 2024


4 Kongresse in einer Veranstaltung

Treffen Sie in München die Fachleute von Chassis, Lenkung, Bremsen sowie Reifen/Räder.
Erweiterte Suche
Anmelden
nach oben

1998 | Buch

Introduction Kapitel lesen Erstes Kapitel lesen

Multiple Criteria Decision Support in Engineering Design

verfasst von: Professor Pratyush Sen, Dr. Jian-Bo Yang

Verlag: Springer London

Enthalten in: Professional Book Archive

Einloggen, um Zugang zu erhalten
insite
SUCHEN

Über dieses Buch

Multiple Criteria Decision Support in Engineering Design examines some of the underlying issues and related modelling strategies, with a view to exploring the rich potential of a generalised multiple-criteria approach to design decision-making. The arguments are supported by numerical examples. It can be argued that, within the classic monocriterion paradigm, the optimal solution is inarguably identified once the feasible alternatives are established and an objective function agreed on. It is only when conflict resolution is involved that decision-making truly becomes important, and many design situations exist where stated functional requirements may be in actual or potential conflict. The most preferred solution under such circumstances depends on the designer's or decision-maker's priorities, so that the chosen solution is based on a combination of technical possibilities and designer preferences. This book addresses the key concepts in multiple criteria decision-making and provides valuable insight into how such problems arise and can be solved, in the area of decision-making in general and in the domain of engineering design in particular.

Inhaltsverzeichnis

Frontmatter
1. Introduction
Abstract
Decision making of all kinds involves the choice of one or more alternatives from a list of options. The list of options would normally all be more or less acceptable solutions for the problem at hand and consequences, both good and bad, flow from the exercise of choice. The aim of rational decision making, therefore, is to maximise the positive consequences and minimise the negative ones. As these consequences are directly related to the decision made or option chosen, it is not unreasonable to treat the consequences as aspects of performance. The decision problem then becomes a matter of considering these aspects of performance of all the options available simultaneously so that the decision maker (DM) can exercise his choice. In other words, rational decision making involves choice within the context of multiple measures of performance or multiple criteria.
Pratyush Sen, Jian-Bo Yang
2. MCDM and the Nature of Decision Making in Design
Abstract
In Chapter 1 a brief outline is provided of the motivation behind the use of multiple criteria decision making (MCDM) techniques. Decision making, in general, and in engineering design, in particular, can be helpfully visualised as a collection of activities that relate to choice in the context of competing technical or functional requirements. The options may either be available and finite in number, as in consulting a catalogue, or they may need to be synthesised, as in engineering design. In any event, the implicit assumption that is often made is that the requirements in question are mutually compatible. This is the domain of classical optimisation in that it is being taken for granted that the stated requirements are mutually compatible or can be made so, although even in classical optimisation there is an implicit acknowledgement of conflict in only being able to design for a stated scenario.
Pratyush Sen, Jian-Bo Yang
3. Multiple Attribute Decision Making
Abstract
A multiple attribute decision making (simply MADM) problem usually comprises a finite number of explicitly given alternative designs and a set of performance attributes. Design selection involves either choosing the most favourable design from the alternative set or ranking all the alternative designs with regard to all attributes. A MADM problem may have either qualitative or quantitative data. More generally, MADM problems may involve both types of data, and approaches for dealing with these will be investigated in Section 3.4.
Pratyush Sen, Jian-Bo Yang
4. Multiple Objective Decision Making
Abstract
A multiobjective optimisation problem may generally be represented as the following vector mathematical programming problem
$$ MOP\left\{ {\begin{array}{*{20}{c}} {optimise{\mkern 1mu} F(X) = \{ {{f}_{1}}(X) \cdots {{f}_{i}}(X) \cdots {{f}_{k}}(X)\} } \\ {subject{\mkern 1mu} to{\mkern 1mu} X \in \Omega } \\ \end{array} } \right. $$
(4.1)
$$ \begin{array}{*{20}{c}} {\Omega = } & {\left\{ {X\left| {\left. {\begin{array}{*{20}{c}} {\begin{array}{*{20}{c}} {{{g}_{i}}(X)0} & {i = 1, \cdots ,{{m}_{1}}} \\ \end{array} } \\ {\begin{array}{*{20}{c}} {{{h}_{j}}(X) = 0} & {j = 1, \cdots ,{{m}_{2}}} \\ \end{array} } \\ {X = {{{\left[ {{{x}_{1}} \cdots {{x}_{n}}} \right]}}^{T}}} \\ \end{array} } \right\}} \right.} \right.} \\ \end{array} $$
where x i , is a decision variable, X denotes a solution, f i (X) is generally a nonlinear objective function, respectively, and g i (X) and h j (X) are nonlinear inequality and equality constraint functions. These objectives are usually incommensurate and in conflict with one another. Therefore there normally exist infinite number of efficient (noninferior, non-dominated or Pareto-optimal) solutions in the MOP. The problem is how to search for a best compromise solution with these multiple objectives being considered simultaneously.
Pratyush Sen, Jian-Bo Yang
5. Multiple Criteria Decision Making and Genetic Algorithms
Abstract
In all of the decision-making methods that have been considered so far, the implicit assumption is that the computational aspects of the problem can be handled satisfactorily. This is often a reasonable assumption, but not necessarily so. This is because the search for the “best solution” in real life in the presence of multiple criteria or measures of performance is often significantly and indeed critically influenced by the ability to assess the effect of design changes on system performance. Difficulties may arise because the mathematical models used for such purposes are possibly discontinuous. Moreover, the performance landscape may not necessarily be single-peaked (or unimodal). This essentially means that one needs a robust optimisation method that can cope with noisy, multi-peaked performance relations with discontinuities in them, in recognition of the fact that real life problems often present themselves in these inconvenient forms.
Pratyush Sen, Jian-Bo Yang
6. An Integrated Multiple Criteria Decision Support System
Abstract
In the previous chapters, we have discussed various MCDM techniques. Each of those techniques may be applied to deal with a different design decision problem on an individual basis. It is, however, of significant advantage that those techniques be incorporated into a software system in an integrated manner, so that the decision maker could use such a system to investigate his decision problems using several methods without being bothered by the mathematics involved.
Pratyush Sen, Jian-Bo Yang
7. Past, Present and the Future
Abstract
The preceding chapters set out the benefits associated with the application of MCDM in engineering design and examine how the use of different methods leads to results of a correspondingly distinctive nature. The data requirements for the various approaches are also discussed along with the underlying assumptions that are built in. As in all decision making methodologies there are two principal considerations in doing this. These are
(i)
how can one make rational decisions in a consistent manner when faced with multiple, conflicting criteria?
 
(ii)
what do real decision-makers do when confronted with decisions involving multiple, conflicting criteria?
 
The first of the two considerations addresses the normative issues of decision making. The aim is to establish more or less standard approaches to broad classes of problems so that the decisions are consistently arrived at. This has the added virtue of allowing computer based decision support tools to be prepared with some degree of confidence in that they will be used in a generally predictable manner. The second of the considerations above deals with the descriptive aspects of decision-making. In other words it is largely about the capturing of the rules applied by real DMs when confronted with real problems.
Pratyush Sen, Jian-Bo Yang
Backmatter
Metadaten
Titel
Multiple Criteria Decision Support in Engineering Design
verfasst von
Professor Pratyush Sen
Dr. Jian-Bo Yang
Copyright-Jahr
1998
Verlag
Springer London
Electronic ISBN
978-1-4471-3020-8
Print ISBN
978-1-4471-3022-2
DOI
https://doi.org/10.1007/978-1-4471-3020-8