Theory of Multiobjective Optimization¶
Sawaragi, Y., Nakayama, & Tanino, T. (1985). Theory of Multiobjective Optimization. Academic Press.
Cited by¶
1 citation across 1 artifact.
Each citation links to the sentence it supports in the citing article.
Primes¶
- Multiobjective Optimization
- Complexity-management costs include: frontier computation can be expensive (particularly for many-objective problems or problems with expensive objective evaluations); frontier visualization degrades with dimensionality (two-to-three objective problems support clean visualization; higher-dimensional fronts require more sophisticated tools); and the preference-articulation problem is genuine and non-trivial — the structure of the Pareto set does not by itself tell decision-makers which point to prefer, as Sawaragi, Nakayama, and Tanino (1985) develop in the foundational theory of multiobjective optimization.
This sourceFoundational mathematical treatment of multiobjective optimization: vector optimization theory, preference structures, and the genuine difficulty of preference articulation in selecting from the Pareto set.
- Complexity-management costs include: frontier computation can be expensive (particularly for many-objective problems or problems with expensive objective evaluations); frontier visualization degrades with dimensionality (two-to-three objective problems support clean visualization; higher-dimensional fronts require more sophisticated tools); and the preference-articulation problem is genuine and non-trivial — the structure of the Pareto set does not by itself tell decision-makers which point to prefer, as Sawaragi, Nakayama, and Tanino (1985) develop in the foundational theory of multiobjective optimization.
Verification¶
This reference passed the adversarial substantiation pipeline: it was checked to exist and to support the claim it is attached to. See how references were verified.
Registry ID ref:29c14911ecdd · see in the full table