MOMCMC: an efficient Monte Carlo method for multi-objective sampling over real parameter space

DOI10.1016/j.camwa.2012.09.003zbMath1268.65002OpenAlexW2170401728MaRDI QIDQ356363

Yaohang Li

Publication date: 25 July 2013

Published in: Computers \& Mathematics with Applications (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.camwa.2012.09.003

zbMATH Keywords

convergenceMarkov chain Monte CarloPareto optimal frontmulti-objective sampling

Mathematics Subject Classification ID

Computational methods in Markov chains (60J22) Monte Carlo methods (65C05)

Uses Software

• MOEA/D
• SPEA2
• Borg

Cites Work

• Optimization by Simulated Annealing
• Hypervolume-based multiobjective optimization: theoretical foundations and practical implications
• Differential evolution -- a simple and efficient heuristic for global optimization over continuous spaces
• Annealing Markov Chain Monte Carlo with Applications to Ancestral Inference
• Equation of State Calculations by Fast Computing Machines
• Evolutionary Algorithms for Solving Multi-Objective Problems
• Monte Carlo sampling methods using Markov chains and their applications
• Monte Carlo strategies in scientific computing
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