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Constrained Multiobjective Nonlinear Optimization: A User Preference Enabling Method
Author(s) -
Shuo Wang,
HsiaoDong Chiang
Publication year - 2018
Publication title -
ieee transactions on cybernetics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.109
H-Index - 124
eISSN - 2168-2275
pISSN - 2168-2267
DOI - 10.1109/tcyb.2018.2833281
Subject(s) - mathematical optimization , multi objective optimization , computer science , preference , complement (music) , nonlinear system , range (aeronautics) , pareto principle , nonlinear programming , constrained optimization , optimization problem , mathematics , engineering , biochemistry , statistics , chemistry , physics , quantum mechanics , complementation , gene , phenotype , aerospace engineering
A novel user preference enabling (UPE) method is developed to solve general constrained nonlinear multiple objective optimization (MOO) problems. User wish lists on the preferred range of each objective function are introduced and incorporated into the MOO formulation to form a user-preferred (UP) MOO problem. A theoretical foundation of the UP feasible region of MOO problems is developed. The developed theoretical work leads to the development of a UPE method for effectively solving the UP-MOO problems. Distinguishing features of the proposed method include its ability to compute a targeted Pareto solution and to serve as a complement to existing MOO methods, in the sense that the proposed method assists the existing MOO methods in computing the Pareto front by providing feasible solutions and UP feasible solutions. Both proposed UPE method and derived theoretical developments are evaluated on several test systems with promising results.

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