Stochastic discrete optimization

We develop new Markov chain Monte Carlo samplers for neighborhood generation in global optimization algorithms based on Hit-and-Run. The success of Hit-and-Run as a sampler on continuous domains motivated Discrete Hit-and-Run with random biwalk for ...

Enhanced PSO with levy flight.Random walk of the particles.High convergence rate.Provides solution accuracy and robust. Hüseyin Haklı and Harun Uguz (2014) proposed a novel approach for global function optimization using particle swarm optimization with ...

Graphical abstractDisplay Omitted HighlightsA new global optimization meta-heuristic inspired by galactic motion is proposed.The proposed algorithm employs alternating phases of exploration and exploitation.Performance on rotated and shifted versions of ...