Hybridisation of real-code population-based incremental learning and differential evolution for multiobjective design of trusses

Author:

Pholdee Nantiwat,Bureerat Sujin

Publisher

Elsevier BV

Subject

Artificial Intelligence,Information Systems and Management,Computer Science Applications,Theoretical Computer Science,Control and Systems Engineering,Software

Reference57 articles.

1. Efficient evolutionary approach to approximate the Pareto-optimal set in multiobjective optimization;Aittokoski;UPS-EMOA, Optimization Method and Software,2010

2. S. Baluja, Population-Based Incremental Learning: A Method for Integrating Genetic Search Based Function Optimization and Competitive Learning, Technical Report CMU_CS_95_163, Carnegie Mellon University, 1994.

3. A simulated annealing-based multiobjective optimization algorithm: AMOSA;Bandyopadhyay;IEEE Transactions on Evolutionary Computation,2008

4. Self-adaptive differential evolution algorithm using population size reduction and three strategies;Brest;Soft Computing – A Fusion of Foundations, Methodologies and Applications,2011

5. Population-based incremental learning for multiobjective optimisation;Bureerat;Advances in Soft Computing,2007

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