Version 1
: Received: 16 August 2022 / Approved: 17 August 2022 / Online: 17 August 2022 (09:47:59 CEST)
How to cite:
Saha, D.; Sallam, K.M.; De, S.; Mohamed, A.W. CHAGSKODE Algorithm for Solving Real World Constrained Optimization Problems. Preprints2022, 2022080314. https://doi.org/10.20944/preprints202208.0314.v1
Saha, D.; Sallam, K.M.; De, S.; Mohamed, A.W. CHAGSKODE Algorithm for Solving Real World Constrained Optimization Problems. Preprints 2022, 2022080314. https://doi.org/10.20944/preprints202208.0314.v1
Saha, D.; Sallam, K.M.; De, S.; Mohamed, A.W. CHAGSKODE Algorithm for Solving Real World Constrained Optimization Problems. Preprints2022, 2022080314. https://doi.org/10.20944/preprints202208.0314.v1
APA Style
Saha, D., Sallam, K.M., De, S., & Mohamed, A.W. (2022). CHAGSKODE Algorithm for Solving Real World Constrained Optimization Problems. Preprints. https://doi.org/10.20944/preprints202208.0314.v1
Chicago/Turabian Style
Saha, D., Shuvodeep De and Ali W. Mohamed. 2022 "CHAGSKODE Algorithm for Solving Real World Constrained Optimization Problems" Preprints. https://doi.org/10.20944/preprints202208.0314.v1
Abstract
Real-world optimization problems are often gov-erned by one or more constraints. Over the last few decades,extensive research has been performed in Constrained Opti-mization Problems (COPs) fueled by advances in computationalpower.Inparticular,EvolutionaryAlgorithms(EAs)areapreferred tool for practitioners for solving these COPs withinpracticable time limits. We propose a novel hybrid EvolutionaryAlgorithm based on the Differential Evolution algorithm andAdaptiveParameterGainingSharingKnowledge-basedalgo-rithm to solve global real-world constrained parameter space.The proposedCHAGSKODEalgorithm leverages the power ofmultiple adaptation strategies concerning the control parameters,search mechanisms, as well as uses knowledge sharing betweenjunior and senior phases. We test our method on the benchmarkfunctions taken from the CEC2020 special session & competitiononreal-worldconstrainedoptimization.ExperimentalresultsindicatethatCHAGSKODEisabletoachievestate-of-the-art performance on real-world constrained global optimizationwhen compared against other well-known real-world constrainedoptimizers.
Computer Science and Mathematics, Data Structures, Algorithms and Complexity
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
