On modification of population-based search algorithms for convergence in stochastic combinatorial optimization

DOI10.1080/02331934.2014.883511zbMath1337.90053OpenAlexW2010702499MaRDI QIDQ2808309

Hyeong Soo Chang

Publication date: 23 May 2016

Published in: Optimization (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/02331934.2014.883511

zbMATH Keywords

convergencemulti-armed banditstochastic combinatorial optimization

Mathematics Subject Classification ID

Numerical mathematical programming methods (65K05) Stochastic programming (90C15) Combinatorial optimization (90C27) Stochastic learning and adaptive control (93E35)

Cites Work

• Recent trends in metaheuristics for stochastic combinatorial optimization
• Asymptotically efficient adaptive allocation rules
• Convergence results for single-step on-policy reinforcement-learning algorithms
• Simulated annealing for noisy cost functions
• Efficient algorithms for online decision problems
• The Sample Average Approximation Method for Stochastic Discrete Optimization
• Ordinal optimisation and simulation
• Evolutionary Policy Iteration Under a Sampling Regime for Stochastic Combinatorial Optimization
• Finite-time analysis of the multiarmed bandit problem

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