optimization theory


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optimization theory

[‚äp·tə·mə′zā·shən ‚thē·ə·rē]
(mathematics)
The specific methodology, techniques, and procedures used to decide on the one specific solution in a defined set of possible alternatives that will best satisfy a selected criterion; includes linear and nonlinear programming, stochastic programming, and control theory. Also known as mathematical programming.
References in periodicals archive ?
Fang, "Solvability of variational inequality problems," Journal of Optimization Theory and Applications, vol.
Sakawa, "Stackelberg solutions to multiobjective two-level linear programming problems," Journal of Optimization Theory and Applications, vol.
Wu, "[epsilon]-weak minimal solutions of vector optimization problems with set-valued maps," Journal of Optimization Theory and Applications, vol.
Yabe, "Globally convergent three-term conjugate gradient methods that use secant conditions and generate descent search directions for unconstrained optimization," Journal of Optimization Theory and Applications, vol.
Distributed optimization theory and application has become one of the important development directions of current system and control science.
Based on the results of the optimization theory, Narang suggests that regional nuclear weapon states might use nuclear weapons as a catalyst for involving major powers in regional conflicts, as an escalation in response to conventional warfare threatening the nation, or as assured retaliation against an adversarial nuclear strike.
Two-person second-order games, Part 1: formulation and transition anatomy, Journal of Optimization Theory and Applications 141(3): 619-639.
Watanabe, "Optimal trajectories of the innovation process and their matching with econometric data," Journal of Optimization Theory and Applications, vol.
There are three mathematical formulations that are usually referred to in optimization theory, each of which seems to be suitable for some types of optimization problems: calculus of variations, Pontryagin maximum principle, and dynamic programming.
Teo, "Lower-order penalization approach to nonlinear semidefinite programming," Journal of Optimization Theory and Applications, vol.
Agarwal, "Sufficiency and duality in multiobjective programming under generalized type i functions," Journal of Optimization Theory and Applications, vol.

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