Decisions with Multiple Objectives¶
Keeney, R. L., & Raiffa, H. (1976). Decisions with Multiple Objectives: Preferences and Value Tradeoffs. Wiley.
Cited by¶
9 citations across 9 artifacts.
Each citation links to the sentence it supports in the citing article.
Primes¶
- Commensurability
- A hospital administrator facing decisions about allocating a bounded budget across oncology, pediatrics, emergency care, and research can do so only if these departments are commensurized (all translated into cost per life-year saved, or cost per patient served, or some other metric), an approach Keeney and Raiffa (1976) formalized as multi-attribute utility theory for collapsing high-dimensional decision problems into tractable scalar objectives.
This sourceCanonical multi-attribute utility theory: develops additive and multiplicative value functions over heterogeneous attributes (cost, performance, aesthetics, safety) to make trade-offs between incommensurable objectives explicit and tractable; supports the manages-complexity claim about collapsing high-dimensional decisions into a scalar objective.
Supported in partVerified against the publisher's abstract
The book's abstract establishes MAUT's project of making trade-offs among incommensurable objectives explicit; it omits the hospital budget example and the 'only if' necessity.
“This book describes how a confused decision maker, who wishes to make a reasonable and responsible choice among alternatives, can systematically probe his true feelings in order to make those critically important, vexing trade-offs between incommensurable objectives.”
- A hospital administrator facing decisions about allocating a bounded budget across oncology, pediatrics, emergency care, and research can do so only if these departments are commensurized (all translated into cost per life-year saved, or cost per patient served, or some other metric), an approach Keeney and Raiffa (1976) formalized as multi-attribute utility theory for collapsing high-dimensional decision problems into tractable scalar objectives.
- Decision
- This frames the problem, bounds analytical scope, and makes trade-offs visible — a multi-criteria decomposition Keeney and Raiffa (1976) formalized in their canonical treatment of decisions with multiple objectives.
This sourceCanonical multi-attribute utility theory: additive and multiplicative value functions over heterogeneous attributes to make trade-offs explicit.
Supported in partVerified against the publisher's abstract
The book's own abstract documents multiple conflicting objectives and the systematic making of trade-offs between incommensurable objectives, but says nothing about framing a problem or bounding analytical scope.
“This book describes how a confused decision maker, who wishes to make a reasonable and responsible choice among alternatives, can systematically probe his true feelings in order to make those critically important, vexing trade-offs between incommensurable objectives.”
- This frames the problem, bounds analytical scope, and makes trade-offs visible — a multi-criteria decomposition Keeney and Raiffa (1976) formalized in their canonical treatment of decisions with multiple objectives.
- Multiobjective Optimization
- Not free of preference-articulation — whether preferences are articulated up front (weights, priorities, goals), after seeing results (a-posteriori), or interactively, preference articulation is required to select a single solution from the Pareto set. Not appropriate when objectives are commensurable and reducible — if objectives can be legitimately converted to a common unit (e.g., all monetary, or all utility), collapsing to single-objective optimization may be appropriate and simpler. Not purely a technical method — in multi-stakeholder contexts, multiobjective optimization is as much a communication and negotiation framework as a computational one, an orientation Keeney and Raiffa (1976) crystallized in their multi-attribute decision-analysis program.
This sourceCanonical multi-attribute utility theory (MAUT) text: develops additive and multiplicative value functions over heterogeneous attributes (cost, performance, aesthetics, safety) to make implicit trade-offs explicit and tractable.
Supported in partVerified against the publisher's abstract
The book's abstract supports MOO as systematic articulation of preferences and trade-offs among incommensurable objectives, but does not itself state a communication or negotiation framing.
“This book describes how a confused decision maker, who wishes to make a reasonable and responsible choice among alternatives, can systematically probe his true feelings in order to make those critically important, vexing trade-offs between incommensurable objectives. The theory is illustrated by many real concrete examples taken from a host of disciplinary settings. The standard approach in decision theory or …”
- Not free of preference-articulation — whether preferences are articulated up front (weights, priorities, goals), after seeing results (a-posteriori), or interactively, preference articulation is required to select a single solution from the Pareto set. Not appropriate when objectives are commensurable and reducible — if objectives can be legitimately converted to a common unit (e.g., all monetary, or all utility), collapsing to single-objective optimization may be appropriate and simpler. Not purely a technical method — in multi-stakeholder contexts, multiobjective optimization is as much a communication and negotiation framework as a computational one, an orientation Keeney and Raiffa (1976) crystallized in their multi-attribute decision-analysis program.
- Preference Heterogeneity and Conflict
- Trade-off situations in design and engineering: User-interface designers balance complexity and simplicity (power users want advanced features, novices want ease of use); software architects balance consistency and flexibility (standardization supports coordination, customization supports heterogeneous needs); urban planners balance density and open space (residents want affordable housing proximity, others want parks and greenery); supply chain managers balance cost and resilience (cost minimization favors concentrated suppliers, risk management favors redundancy), trade-offs Keeney and Raiffa (1976) formalize as multi-attribute decision problems with conflicting objectives.
This sourceCanonical multi-attribute utility theory (MAUT) text: develops additive and multiplicative value functions over heterogeneous attributes (cost, performance, aesthetics, safety) to make implicit trade-offs explicit and tractable.
Supported in partVerified against the publisher's abstract
Abstract only: K&R's own abstract states trade-offs between incommensurable, conflicting objectives, backing the formalization clause but not the four domain illustrations.
“Many of the complex problems faced by decision makers involve multiple conflicting objectives. This book describes how a confused decision maker, who wishes to make a reasonable and responsible choice among alternatives, can systematically probe his true feelings in order to make those critically important, vexing trade-offs between incommensurable objectives.”
- Trade-off situations in design and engineering: User-interface designers balance complexity and simplicity (power users want advanced features, novices want ease of use); software architects balance consistency and flexibility (standardization supports coordination, customization supports heterogeneous needs); urban planners balance density and open space (residents want affordable housing proximity, others want parks and greenery); supply chain managers balance cost and resilience (cost minimization favors concentrated suppliers, risk management favors redundancy), trade-offs Keeney and Raiffa (1976) formalize as multi-attribute decision problems with conflicting objectives.
- Value Commensuration
- This commensuration is often implicit, embedded in feature selection and trade-off decisions, but Keeney and Raiffa (1976) supply the canonical multi-attribute utility framework for making such trade-offs explicit through additive or multiplicative value functions over heterogeneous attributes.
This sourceCanonical multi-attribute utility theory (MAUT) text: develops additive and multiplicative value functions over heterogeneous attributes (cost, performance, aesthetics, safety) to make implicit trade-offs explicit and tractable.
Supported in partVerified against the publisher's abstract
The publisher abstract confirms the book's subject is systematic trade-offs among multiple conflicting objectives, but not the specific additive or multiplicative value-function apparatus the claim names.
“This book describes how a confused decision maker, who wishes to make a reasonable and responsible choice among alternatives, can systematically probe his true feelings in order to make those critically important, vexing trade-offs between incommensurable objectives.”
- This commensuration is often implicit, embedded in feature selection and trade-off decisions, but Keeney and Raiffa (1976) supply the canonical multi-attribute utility framework for making such trade-offs explicit through additive or multiplicative value functions over heterogeneous attributes.
Mechanisms¶
- Multi-Path Disposition Matrix
- This is the standing hazard of any multi-criteria decision analysis
This sourceMakes multiattribute weights and scaling constants depend on elicited preferences and value tradeoffs rather than objective measurement alone.
- This is the standing hazard of any multi-criteria decision analysis
- Weighted Scoring Overlay
- Its strength is legitimacy through transparency: it forces the value judgment into stated, contestable numbers, so a decision can be defended, audited, and revised when values change — and it lets stakeholders argue about weights (which is the real disagreement) instead of about a mysterious verdict.
This sourceFormalizes preferences and value tradeoffs as explicit quantitative attributes, scaling constants, and multiattribute utility functions.
- Its strength is legitimacy through transparency: it forces the value judgment into stated, contestable numbers, so a decision can be defended, audited, and revised when values change — and it lets stakeholders argue about weights (which is the real disagreement) instead of about a mysterious verdict.
- Weighted Scoring Rubric
- Compute the composite. Multiply each anchored rating by its weight and sum (a weighted additive model
This sourceDefines a weighted additive model that sums weighted attribute ratings into total option scores used to rank alternatives.
- Compute the composite. Multiply each anchored rating by its weight and sum (a weighted additive model
- Weighted Sum Objective
- Its failure mode is false commensurability
This sourceShows that an additive weighted objective encodes explicit rates of tradeoff among objectives on a common value scale.
- Its failure mode is false commensurability
Verification¶
Does it exist? Confirmed. This work's DOI resolves to a registered record, which fixes its identity. That is all it fixes.
Does it back the claim? Read against the text for 5 of 9 citations: 5 supported in part. Each verdict is shown under its citation below, with what in the work backs the sentence.
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Links previously used in the corpus¶
Before the registry existed this work was also linked 4 other ways.
- https://search.worldcat.org/title/2119417 ×2
- https://books.google.com/books/about/Decisions_with_Multiple_Objectives.html?id=k_x9AAAAIAAJ ×1
- https://books.google.com/books?id=k_x9AAAAIAAJ ×1
- https://www.google.com/books/edition/Decisions_with_Multiple_Objectives/GPE6ZAqGrnoC ×1
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