matlab program fmincon Search Results


sequential quadratic programming sqp procedure  (MathWorks Inc)
96
MathWorks Inc sequential quadratic programming sqp procedure
The environment to traverse ( A ) and the simulation pipeline ( B ). The environment was generated as a linear combination of scaled and translated Gaussian surfaces, as described in Methods and Materials. The simulation procedure entailed refining the path predictions by each algorithm separately using the landscape-dependent cost function. Abbreviations: GA—genetic Algorithm; PSO—Particle Swarm Optimization; <t>SQP—</t> Sequential Quadratic Programming; a.u.—arbitrary units.
Sequential Quadratic Programming Sqp Procedure, supplied by MathWorks Inc, used in various techniques. Bioz Stars score: 96/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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mathworks matlab software  (MathWorks Inc)
96
MathWorks Inc mathworks matlab software
The environment to traverse ( A ) and the simulation pipeline ( B ). The environment was generated as a linear combination of scaled and translated Gaussian surfaces, as described in Methods and Materials. The simulation procedure entailed refining the path predictions by each algorithm separately using the landscape-dependent cost function. Abbreviations: GA—genetic Algorithm; PSO—Particle Swarm Optimization; <t>SQP—</t> Sequential Quadratic Programming; a.u.—arbitrary units.
Mathworks Matlab Software, supplied by MathWorks Inc, used in various techniques. Bioz Stars score: 96/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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comsol multiphysics  (COMSOL Inc)
90
COMSOL Inc comsol multiphysics
The environment to traverse ( A ) and the simulation pipeline ( B ). The environment was generated as a linear combination of scaled and translated Gaussian surfaces, as described in Methods and Materials. The simulation procedure entailed refining the path predictions by each algorithm separately using the landscape-dependent cost function. Abbreviations: GA—genetic Algorithm; PSO—Particle Swarm Optimization; <t>SQP—</t> Sequential Quadratic Programming; a.u.—arbitrary units.
Comsol Multiphysics, supplied by COMSOL Inc, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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npsol  (Stanford Business Software Inc)
90
Stanford Business Software Inc npsol
The environment to traverse ( A ) and the simulation pipeline ( B ). The environment was generated as a linear combination of scaled and translated Gaussian surfaces, as described in Methods and Materials. The simulation procedure entailed refining the path predictions by each algorithm separately using the landscape-dependent cost function. Abbreviations: GA—genetic Algorithm; PSO—Particle Swarm Optimization; <t>SQP—</t> Sequential Quadratic Programming; a.u.—arbitrary units.
Npsol, supplied by Stanford Business Software Inc, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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tomlab optimization toolbox  (Tomlab Optimization)
90
Tomlab Optimization tomlab optimization toolbox
The environment to traverse ( A ) and the simulation pipeline ( B ). The environment was generated as a linear combination of scaled and translated Gaussian surfaces, as described in Methods and Materials. The simulation procedure entailed refining the path predictions by each algorithm separately using the landscape-dependent cost function. Abbreviations: GA—genetic Algorithm; PSO—Particle Swarm Optimization; <t>SQP—</t> Sequential Quadratic Programming; a.u.—arbitrary units.
Tomlab Optimization Toolbox, supplied by Tomlab Optimization, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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findmaximum  (Wolfram Research)
90
Wolfram Research findmaximum
The environment to traverse ( A ) and the simulation pipeline ( B ). The environment was generated as a linear combination of scaled and translated Gaussian surfaces, as described in Methods and Materials. The simulation procedure entailed refining the path predictions by each algorithm separately using the landscape-dependent cost function. Abbreviations: GA—genetic Algorithm; PSO—Particle Swarm Optimization; <t>SQP—</t> Sequential Quadratic Programming; a.u.—arbitrary units.
Findmaximum, supplied by Wolfram Research, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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Image Search Results


The environment to traverse ( A ) and the simulation pipeline ( B ). The environment was generated as a linear combination of scaled and translated Gaussian surfaces, as described in Methods and Materials. The simulation procedure entailed refining the path predictions by each algorithm separately using the landscape-dependent cost function. Abbreviations: GA—genetic Algorithm; PSO—Particle Swarm Optimization; SQP— Sequential Quadratic Programming; a.u.—arbitrary units.

Journal: bioRxiv

Article Title: Evaluating Evolutionary and Gradient-Based Algorithms for Optimal Pathfinding

doi: 10.1101/2025.03.16.643541

Figure Lengend Snippet: The environment to traverse ( A ) and the simulation pipeline ( B ). The environment was generated as a linear combination of scaled and translated Gaussian surfaces, as described in Methods and Materials. The simulation procedure entailed refining the path predictions by each algorithm separately using the landscape-dependent cost function. Abbreviations: GA—genetic Algorithm; PSO—Particle Swarm Optimization; SQP— Sequential Quadratic Programming; a.u.—arbitrary units.

Article Snippet: The third algorithm used in our study was a quasi-Newton method—the Sequential Quadratic Programming (SQP) procedure (“ fmincon ” function in the MATLAB’s Optimization Toolbox)—described in detail in ( ).

Techniques: Generated, Refining

Representative paths calculated by the three evaluated algorithms: ( A ) Genetic Algorithm (GA), ( B ) Particle Swarm Optimization (PSO), and ( C ) Sequential Quadratic Programming (SQP), each illustrating the distinct pathfinding solutions. Abbreviations are the same as in .

Journal: bioRxiv

Article Title: Evaluating Evolutionary and Gradient-Based Algorithms for Optimal Pathfinding

doi: 10.1101/2025.03.16.643541

Figure Lengend Snippet: Representative paths calculated by the three evaluated algorithms: ( A ) Genetic Algorithm (GA), ( B ) Particle Swarm Optimization (PSO), and ( C ) Sequential Quadratic Programming (SQP), each illustrating the distinct pathfinding solutions. Abbreviations are the same as in .

Article Snippet: The third algorithm used in our study was a quasi-Newton method—the Sequential Quadratic Programming (SQP) procedure (“ fmincon ” function in the MATLAB’s Optimization Toolbox)—described in detail in ( ).

Techniques: