A perturbed martingale approach to global optimization

作者：Sarkar Saikat; Roy Debasish^*; Vasu Ram Mohan

来源：Physics Letters, Section A: General, Atomic and Solid State Physics , 2014, 378(38-39): 2831-2844.

DOI：10.1016/j.physleta.2014.07.044

• Local and global extremization
• Martingale problem
• Random perturbations
• Gain-like additive updates
• Chaotic dynamics

A new global stochastic search, guided mainly through derivative-free directional information computable from the sample statistical moments of the design variables within a Monte Carlo setup, is proposed. The search is aided by imparting to the directional update term additional layers of random perturbations referred to as %26apos;coalescence%26apos; and %26apos;scrambling%26apos;. A selection step, constituting yet another avenue for random perturbation, completes the global search. The direction-driven nature of the search is manifest in the local extremization and coalescence components, which are posed as martingale problems that yield gain-like update terms upon discretization. As anticipated and numerically demonstrated, to a limited extent, against the problem of parameter recovery given the chaotic response histories of a couple of nonlinear oscillators, the proposed method appears to offer a more rational, more accurate and faster alternative to most available evolutionary schemes, prominently the particle swarm optimization.

• 出版日期2014-8-1