Open Access
SPEA2: Improving the Strength Pareto Evolutionary Algorithm For Multiobjective Optimization
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The article was published on 2002-01-01 and is currently open access. It has received 1972 citations till now. The article focuses on the topics: Pareto principle & Multi-objective optimization.read more
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Agricultural and resource economics review
Thomas G. Johnson,Ann Markusen,Seong-Hoon Cho,Seung Gyu Kim,Christopher D. Clark,William M. Park,Vishakha Maskey,Cheryl Brown,Alan R. Collins,Hala F. Nassar,Timothy R. Wojan,Dayton M. Lambert,David A. McGranahan,Todd Gabe,Kristen Colby,Kathleen P. Bell,Marvin T. Batte,Stan Ernst,James F. Oehmke,Satoshi Tsukamoto,Lori A. Post,Steven C. Deller,Victor Lledo,Yohannes G. Hailu +23 more
Journal ArticleDOI
A survey of metaheuristic-based techniques for University Timetabling problems
TL;DR: An overview of metaheuristics in university timetabling applications is carried out, paying particular attention to the various methods that have been proposed for dealing and differentiating between constraints of varying importance.
Journal ArticleDOI
Multiobjective Particle Swarm Algorithm With Fuzzy Clustering for Electrical Power Dispatch
TL;DR: A fuzzy clustering-based particle swarm (FCPSO) algorithm has been proposed to solve the highly constrained EED problem involving conflicting objectives and was able to provide a satisfactory compromise solution in almost all the trials, validating the efficacy and applicability of the proposed approach over the real-world multiobjective optimization problems.
Journal ArticleDOI
IGD Indicator-Based Evolutionary Algorithm for Many-Objective Optimization Problems
Yanan Sun,Gary G. Yen,Zhang Yi +2 more
TL;DR: An IGD indicator-based evolutionary algorithm for solving many-objective optimization problems (MaOPs) is proposed and experimental results measured by the chosen performance metrics indicate that the proposed algorithm is very competitive in addressing MaOPs.
Proceedings ArticleDOI
Combining Model-based and Genetics-based Offspring Generation for Multi-objective Optimization Using a Convergence Criterion
TL;DR: The proposed hybrid method is verified on widely used test problems and simulation results show that the method is effective in achieving Pareto-optimal solutions compared to two state-of-the-art evolutionary multi-objective algorithms.