Decision Support Systems
Models and tools that help people make well-informed decisions in complex, uncertain settings.
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Multi-Objective Evolutionary Algorithms for Engineering Shape Design
K Deb, T Goel. Cited by 42
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Classification of adaptive memetic algorithms: a comparative study
YS Ong, M Lim, N Zhu, KW Wong. Cited by 515
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Computational Capabilities of Soft-Computing Frameworks: An Overview
NS Chaudhari, YS Ong, V Trivedi. Cited by 2
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Dual Guidance in Evolutionary Multi-objective Optimization by Localization
LT Bui, K Deb, HA Abbass, D Essam. Cited by 5
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Practical optimization using evolutionary methods
K Deb. Cited by 8
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Monotonicity Analysis, Evolutionary Multi-objective Optimization, and Discovery of Design Principles
K Deb, A Srinivasan. Cited by 10
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Stochastic Evolutionary Multiobjective Environmental/Economic Dispatch
RTFA King, HCS Rughooputh, K Deb. Cited by 31
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Problem Deflnitions and Evaluation Criteria for the CEC 2006 Special Session on Constrained Real-Parameter Optimization
J Liang, TP Rúnarsson, E Mezura‐Montes, M Clerc, PN Suganthan, CAC Coello, K Deb. Cited by 423
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A Study on Polynomial Regression and Gaussian Process Global Surrogate Model in Hierarchical Surrogate-Assisted Evolutionary Algorithm
Z Zhou, YS Ong, MH Nguyen, D Lim. Cited by 144
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Handling Constraints In Robust Multi-Objective Optimization
H Gupta, K Deb. Cited by 23
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Evaluating the ε-Domination Based Multi-Objective Evolutionary Algorithm for a Quick Computation of Pareto-Optimal Solutions
K Deb, M Mohan, S Mishra. Cited by 638
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A probabilistic cooperative–competitive hierarchical model for global optimization
K Leung, I King, YC Wong. Cited by 5