Paper Info
Title
Differential evolution with self-adaptation and local search for constrained multiobjective optimization
Abstract
This paper presents Differential Evolution with Self-adaptation and Local Search for Constrained Multiobjective Optimization algorithm (DECMOSA-SQP), which uses the self-adaptation mechanism from DEMOwSA algorithm presented at CEC 2007 and a SQP local search. The constrained handling mechanism is also incorporated in the new algorithm. Assessment of the algorithm using CEC 2009 special session and competition on constrained multiobjective optimization test functions is presented. The functions are composed of unconstrained and constrained problems. Their results are assessed using the IGD metric. Based on this metric, algorithm strengths and weaknesses are discussed.
Year
DOI
Venue
2009
10.1109/CEC.2009.4982948
IEEE Congress on Evolutionary Computation
Keywords
Field
DocType
differential evolution,constrained multiobjective optimization algorithm,special session,multiobjective optimization test function,local search,algorithm strength,self-adaptation mechanism,new algorithm,demowsa algorithm,sqp local search,evolutionary computation,computer architecture,computational modeling,computer science,simulated annealing,optimization,constraint optimization,testing,multiobjective optimization,quadratic programming,chromium,approximation algorithms
Simulated annealing,Approximation algorithm,Mathematical optimization,Computer science,Evolutionary computation,Multi-objective optimization,Differential evolution,Artificial intelligence,Local search (optimization),Quadratic programming,Machine learning,Constrained optimization
Conference
Citations 
PageRank 
References 
44
1.26
25
Authors
4
Name
Order
Citations
PageRank
Ales Zamuda140018.26
Janez Brest2219090.76
Borko Bošković334317.09
Viljem Žumer430919.95