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Proceedings of the 2000 American Control Conference. ACC (IEEE Cat. No.00CH36334), 2000
For discrete-time control-affine systems on an infinite interval, an analytical solution of the greedy optimal control problem is presented. The "greedy" formulation of the optimal control problem calls for minimization of the instantaneous cost function, rather than the cumulative one, as in the conventional optimal control.
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For discrete-time control-affine systems on an infinite interval, an analytical solution of the greedy optimal control problem is presented. The "greedy" formulation of the optimal control problem calls for minimization of the instantaneous cost function, rather than the cumulative one, as in the conventional optimal control.
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Automatica, 1969
It is indicated that optimal stochastic control is still in its infancy, and that at the present time it has little use in practice although a wide class of problems can be precisely stated. A brief survey of the problem involved in attempting to formulate and to solve optimal stochastic control problems is discussed along with the corresponding ...
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It is indicated that optimal stochastic control is still in its infancy, and that at the present time it has little use in practice although a wide class of problems can be precisely stated. A brief survey of the problem involved in attempting to formulate and to solve optimal stochastic control problems is discussed along with the corresponding ...
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1973
Recently, a number of general methods for obtaining necessary conditions for optimality have been derived (see [2],[3],[5]). In [4], the author has given a general method, starting from the following basic problem: BP(S,f): “Given a set S in Rn and a function f: Rn →R1 , determine xeS such that f(x) is maximal”.
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Recently, a number of general methods for obtaining necessary conditions for optimality have been derived (see [2],[3],[5]). In [4], the author has given a general method, starting from the following basic problem: BP(S,f): “Given a set S in Rn and a function f: Rn →R1 , determine xeS such that f(x) is maximal”.
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A survey on evolutionary computation for complex continuous optimization
Artificial Intelligence Review, 2021Kay Chen Tan, Zhi-Hui Zhan
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The Arithmetic Optimization Algorithm
Computer Methods in Applied Mechanics and Engineering, 2021Ali Diabat +2 more
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Decomposition-Based Multiobjective Optimization for Constrained Evolutionary Optimization
IEEE Transactions on Systems, Man, and Cybernetics: Systems, 2021Yong Wang +2 more
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Maintenance optimization in industry 4.0
Reliability Engineering and System Safety, 2023Luca Pinciroli +2 more
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Evolutionary Large-Scale Multi-Objective Optimization: A Survey
ACM Computing Surveys, 2022Ran Cheng, Ye Tian, Xingyi Zhang
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