TY - JOUR

T1 - Hesitant adaptive search

T2 - The distribution of the number of iterations to convergence

AU - Wood, G. R.

AU - Zabinsky, Z. B.

AU - Kristinsdottir, B. P.

PY - 2001/2

Y1 - 2001/2

N2 - Hesitant adaptive search is a stochastic optimisation procedure which accommodates hesitation, or pausing, at objective function values. It lies between pure adaptive search (which strictly improves at each iteration) and simulated annealing with constant temperature (which allows backtracking, or the acceptance of worse function values). In this paper we build on an earlier work and make two contributions; first, we link hesitant adaptive search to standard counting process theory, and second, we use this to derive the exact distribution of the number of iterations of hesitant adaptive search to termination.

AB - Hesitant adaptive search is a stochastic optimisation procedure which accommodates hesitation, or pausing, at objective function values. It lies between pure adaptive search (which strictly improves at each iteration) and simulated annealing with constant temperature (which allows backtracking, or the acceptance of worse function values). In this paper we build on an earlier work and make two contributions; first, we link hesitant adaptive search to standard counting process theory, and second, we use this to derive the exact distribution of the number of iterations of hesitant adaptive search to termination.

UR - http://www.scopus.com/inward/record.url?scp=0038203929&partnerID=8YFLogxK

M3 - Article

AN - SCOPUS:0038203929

VL - 89

SP - 479

EP - 486

JO - Mathematical Programming

JF - Mathematical Programming

SN - 0025-5610

IS - 3

ER -