Results 11 to 20 of about 161,542 (309)
Constrained Optimization in Simulation: A Novel Approach [PDF]
SSRN Electronic Journal, 2008 This paper presents a novel heuristic for constrained optimization of random computer simulation models, in which one of the simulation outputs is selected as the objective to be minimized while the other outputs need to satisfy prespeci¯ed target values.
Van Nieuwenhuyse, Inneke +2 more
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Frontiers in Robotics and AI, 2021 This article provides a theory for provably safe and computationally efficient distributed constrained control, and describes an application to a swarm of nano-quadrotors with limited on-board hardware and subject to multiple state and input constraints.
Bryan Convens +6 more
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Dynamic Constrained Boundary Method for Constrained Multi-Objective Optimization
Mathematics, 2022 When solving complex constrained problems, how to efficiently utilize promising infeasible solutions is an essential issue because these promising infeasible solutions can significantly improve the diversity of algorithms.
Qiuzhen Wang +6 more
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On Some Constrained Optimization Problems
Mathematics, 2022 By using appropriate methods of variational analysis, the necessary conditions of optimality are established for new classes of constrained optimization problems involving multiple and curvilinear integral functionals.
Savin Treanţă +3 more
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Optimal Solvers for PDE-Constrained Optimization [PDF]
SIAM Journal on Scientific Computing, 2010 Optimization problems with constraints which require the solution of a partial differential equation arise widely in many areas of the sciences and engineering, in particular in problems of design. The solution of such PDE-constrained optimization problems is usually a major computational task.
Tyrone Rees +2 more
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Omnipredictors for Constrained Optimization
CoRR, 2022 The notion of omnipredictors (Gopalan, Kalai, Reingold, Sharan and Wieder ITCS 2021), suggested a new paradigm for loss minimization. Rather than learning a predictor based on a known loss function, omnipredictors can easily be post-processed to minimize any one of a rich family of loss functions compared with the loss of hypotheses in a class ...
Lunjia Hu +3 more
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Clustering-Based Monarch Butterfly Optimization for Constrained Optimization
International Journal of Computational Intelligence Systems, 2020 Monarch butterfly optimization (MBO) algorithm is a newly-developed metaheuristic approach that has shown striking performance on several benchmark problems.
Sibo Huang +3 more
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Data-driven Harris Hawks constrained optimization for computationally expensive constrained problems
Complex & Intelligent Systems, 2022 Aiming at the constrained optimization problem where function evaluation is time-consuming, this paper proposed a novel algorithm called data-driven Harris Hawks constrained optimization (DHHCO).
Chongbo Fu +3 more
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Constrained Optimal Transport [PDF]
Archive for Rational Mechanics and Analysis, 2017 The classical duality theory of Kantorovich and Kellerer for the classical optimal transport is generalized to an abstract framework and a characterization of the dual elements is provided. This abstract generalization is set in a Banach lattice $\cal{X}$ with a order unit.
Ibrahim Ekren, H. Mete Soner
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International Journal of Computational Intelligence Systems, 2022 The constrained optimization problems can be transformed into multi-objective optimization problems, and thus can be optimized by multi-objective evolutionary algorithms.
Xinsheng Lai
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