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Chapter and Conference Paper
Hybridizing Infeasibility Driven and Constrained-Domination Principle with MOEA/D for Constrained Multiobjective Evolutionary Optimization
This paper presents a novel multiobjective constraint handling approach, named as MOEA/D-CDP-ID, to tackle constrained optimization problems. In the proposed method, two mechanisms, namely infeasibility driven...
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Chapter and Conference Paper
Multi-Factorial Evolutionary Algorithm Based on M2M Decomposition
This paper proposes a decomposition-based multi-objective multi-factorial evolutionary algorithm (MFEA/D-M2M). The MFEA/D-M2M adopts the M2M approach to decompose multi-objective optimization problems into mul...
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Chapter and Conference Paper
Adaptive Recombination Operator Selection in Push and Pull Search for Solving Constrained Single-Objective Optimization Problems
This paper proposes an adaptive method to select recombination operators, including differential evolution (DE) operators and polynomial operators. Moreover, a push and pull search (PPS) method is used to hand...
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Chapter and Conference Paper
TH-GRN Model Based Collective Tracking in Confined Environment
Collective task in swarm robots has been studied widely because of ...
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Chapter and Conference Paper
An Improved Epsilon Method with M2M for Solving Imbalanced CMOPs with Simultaneous Convergence-Hard and Diversity-Hard Constraints
When tackling imbalanced constrained multi-objective optimization problems (CMOPs) with simultaneous convergence-hard and diversity-hard constraints, a critical issue is to balance the diversity and convergenc...