Results 21 to 30 of about 610,742 (235)
Self-Scaling Variable Metric in Constrained Optimization [PDF]
Al-Rafidain Journal of Computer Sciences and Mathematics, 2020 In this paper, we investigated of a new self-scaling by use quasi-Newton method and conjugate gradient method. The new algorithm satisfies a quasi-newton condition and mutually conjugate, and practically proved its efficiency when compared with the well ...
Eman Hamed, Marwa Hamad
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Design of High-Performance Magnetorquer with Air Core for CubeSat [PDF]
Xibei Gongye Daxue Xuebao, 2018 To solve the problem that how to design a big magnetic moment, small size, light weight, low power consumption magnetorquer with air core under the constraint of limited volume and power in CubSate, multiobjective optimization design method is used ...
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Energies, 2022 This paper proposes a modified quasi-opposition-based grey wolf optimization (mQOGWO) method to solve complex constrained optimization problems. The effectiveness of mQOGWO is examined on (i) 23 mathematical benchmark functions with different dimensions ...
Salil Madhav Dubey +2 more
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A constrained multi-objective surrogate-based optimization algorithm [PDF]
, 2014 Surrogate models or metamodels are widely used in the realm of engineering for design optimization to minimize the number of computationally expensive simulations.
Couckuyt, Ivo +3 more
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Constrained Multiobjective Biogeography Optimization Algorithm
The Scientific World Journal, 2014 Multiobjective optimization involves minimizing or maximizing multiple objective functions subject to a set of constraints. In this study, a novel constrained multiobjective biogeography optimization algorithm (CMBOA) is proposed.
Hongwei Mo +4 more
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Sensitivity-Based Change Detection for Dynamic Constrained Optimization
IEEE Access, 2020 In dynamic constrained optimization, changes may occur in either the objective function or constraint functions, or both. However, although research on dynamic optimization has been growing significantly, it is centered mainly around unconstrained ...
Noha Hamza, Ruhul Sarker, Daryl Essam
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Investigated Non-Conic Model for Constrained Optimization [PDF]
Al-Rafidain Journal of Computer Sciences and Mathematics, 2008 In this search, we develop the nonlinear constrained optimization by investigation a new region of solution depending on extended conic model to non-conic model by using conjugate gradient method. The new method is too effective when compared with other
Eman Al-Haj Saeed, Huda Ahmed
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, 2015 Different types of evolutionary algorithms have been developed for constrained continuous optimization. We carry out a feature-based analysis of evolved constrained continuous optimization instances to understand the characteristics of constraints that ...
Neumann, FranK, Poursoltan, Shayan
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MOOSE Optimization Module: Physics-constrained optimization
SoftwareXThe MOOSE Optimization Module integrates optimization capabilities within the MOOSE framework, enabling efficient and accurate physics-constrained optimization. This module leverages automatic differentiation to compute Jacobians and employs an automatic
Zachary M. Prince +4 more
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Atti della Accademia Peloritana dei Pericolanti : Classe di Scienze Fisiche, Matematiche e Naturali, 2020 This is a companion paper to "Ghost penalties in nonconvex constrained optimization: Diminishing stepsizes and iteration complexity" (to appear in Mathematics of Operations Research).
Francisco Facchinei +3 more
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