Titlebook: Robust Design and Assessment of Product and Production by Means of Probabilistic Multi-objective Opt; Maosheng Zheng,Jie Yu Book 2024 The

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Concise Description of Probabilistic Multi-objective Optimization from Viewpoint of System Theory,simultaneous optimization of multiple objectives. From the perspectives of set theory and probability theory, the basic methods of “simultaneous optimization of multiple objectives” in?a system are the?mutual methods such as “intersection” and “joint probability”. Furthermore, the concept of “prefer

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Robust Design of a Single Objective as Dual Sub-objectives Optimization,ation. In the treatment, the arithmetic . of performance utility indicator of the objective of an alternative is taken as one sub-objective, and the . of performance utility indicator is taken as other sub-objective, the dual sub-objectives contribute their part of partial preferable probabilities t

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Robust Design and Assessment of Product and Production with Multiple Objectives,ign problem can be seen as the “dual multi-objective optimization” reasonably; the evaluation for the part of partial preferable probability of mean value is conducted according to the type of the attribute, while the evaluation for the part of partial preferable probability of the dispersion is con

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Robust Design with Sequential Uniform Algorithm for Optimization by Means of PMOO,zation (PMOO) in term of total preferable probability. A series of temportary candidate “optimum statuses” which were produced in the subsequent optimization of sequential uniform algorithm is used to form a “special point set”; the objective responses of “special point set” are evaluated once more

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Concise Description of Probabilistic Multi-objective Optimization from Viewpoint of System Theory,egulated, which characterizes the simultaneity of multi—objective optimization and treats both beneficial type of utility indexes and unbeneficial type of utility indexes of performance indicators equivalently and conformably.

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Robust Design of a Single Objective as Dual Sub-objectives Optimization,ger the better, the smaller the better and target the best, are formulated respectively. Moreover, ranking sequence of total preferable probabilities of alternatives is used to complete the optimization option. Subsequently, some application examples are given.

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Book 2024nses sufficiently for robust design, so an appropriate approach is needed.?..The preference or role of a response in the evaluation is indicated by using preferable probability as the unique index. Thus, the rational approach for robust design and assessment of product and production is formulated b