An Improved Cohort Intelligence with Panoptic Learning Behavior for Solving Constrained Problems

DOI10.1007/978-981-33-6710-4_2OpenAlexW3153781289MaRDI QIDQ5011380

Apoorva S. Shastri, Anand J. Kulkarni, Ganesh Krishnasamy

Publication date: 27 August 2021

Published in: Constraint Handling in Metaheuristics and Applications (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/978-981-33-6710-4_2

zbMATH Keywords

cohort intelligenceunconstrainednature-inspired optimizationconstrained test problemspanoptic learning

Mathematics Subject Classification ID

Approximation methods and heuristics in mathematical programming (90C59) Problem solving in the context of artificial intelligence (heuristics, search strategies, etc.) (68T20)

Uses Software

• NLPQL

Cites Work

• Application of the cohort-intelligence optimization method to three selected combinatorial optimization problems
• Differential evolution in constrained numerical optimization: an empirical study
• An application of swarm optimization to nonlinear programming
• A hybrid particle swarm optimization with a feasibility-based rule for constrained optimization
• An efficient constraint handling method for genetic algorithms
• Cultured differential evolution for constrained optimization
• Derivative-free filter simulated annealing method for constrained continuous global optimization
• Constraint handling in genetic algorithms using a gradient-based repair method
• A piecewise linear chaotic map and sequential quadratic programming based robust hybrid particle swarm optimization
• SOLVING CONSTRAINED OPTIMIZATION PROBLEMS USING PROBABILITY COLLECTIVES AND A PENALTY FUNCTION APPROACH
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