An updated survey of GA-based multiobjective optimization techniques
ACM Computing Surveys (CSUR)
Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms for Multiobjective Optimization: FormulationDiscussion and Generalization
Proceedings of the 5th International Conference on Genetic Algorithms
Some experiments in machine learning using vector evaluated genetic algorithms (artificial intelligence, optimization, adaptation, pattern recognition)
Approximating the Nondominated Front Using the Pareto Archived Evolution Strategy
Evolutionary Computation
Covariance Matrix Adaptation for Multi-objective Optimization
Evolutionary Computation
Muiltiobjective optimization using nondominated sorting in genetic algorithms
Evolutionary Computation
An Evolutionary Metaheuristic for Approximating Preference-Nondominated Solutions
INFORMS Journal on Computing
Group search optimizer: an optimization algorithm inspired by animal searching behavior
IEEE Transactions on Evolutionary Computation
Multiobjective evolutionary algorithms: a comparative case studyand the strength Pareto approach
IEEE Transactions on Evolutionary Computation
A fast and elitist multiobjective genetic algorithm: NSGA-II
IEEE Transactions on Evolutionary Computation
IEEE Transactions on Evolutionary Computation
RM-MEDA: A Regularity Model-Based Multiobjective Estimation of Distribution Algorithm
IEEE Transactions on Evolutionary Computation
A Simulated Annealing-Based Multiobjective Optimization Algorithm: AMOSA
IEEE Transactions on Evolutionary Computation
Dominance-Based Multiobjective Simulated Annealing
IEEE Transactions on Evolutionary Computation
AbYSS: Adapting Scatter Search to Multiobjective Optimization
IEEE Transactions on Evolutionary Computation
U-measure: a quality measure for multiobjective programming
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
A Modified micro Genetic Algorithm for undertaking Multi-Objective Optimization Problems
Journal of Intelligent & Fuzzy Systems: Applications in Engineering and Technology - Recent Advances in Soft Computing: Theories and Applications
Hi-index | 12.05 |
In this paper, a novel multi-objective group search optimizer named NMGSO is proposed for solving the multi-objective optimization problems. To simplify the computation, the scanning strategy of the original GSO is replaced by the limited pattern search procedure. To enrich the search behavior of the rangers, a special mutation with a controlling probability is designed to balance the exploration and exploitation at different searching stages and randomness is introduced in determining the coefficients of members to enhance the diversity. To handle multiple objectives, the non-dominated sorting scheme and multiple producers are used in the algorithm. In addition, the kernel density estimator is used to keep diversity. Simulation results based on a set of benchmark functions and comparisons with some methods demonstrate the effectiveness and robustness of the proposed algorithm, especially for the high-dimensional problems.