Simulation optimization (SO) refers to the optimization of an objective function subject to
constraints, both of which can be evaluated through a stochastic simulation. To address …

Simulated annealing is a probabilistic method proposed in Kirkpatrick, Gelett and Vecchi
(1983) and Cerny (1985) for finding the global minimum of a cost function that may possess …

Nature-Inspired Optimization Algorithms, Second Edition provides an introduction to all
major nature-inspired algorithms for optimization. The book's unified approach, balancing …

Problems with multiple objectives arise in a natural fashion in most disciplines and their
solution has been a challenge to researchers for a long time. Despite the considerable …

Swarm intelligence is a relatively new approach to problem solving that takes inspiration
from the social behaviors of insects and of other animals. In particular, ants have inspired a …

Monte Carlo statistical methods, particularly those based on Markov chains, are now an
essential component of the standard set of techniques used by statisticians. This new edition …

The idea for this book came from the time the authors spent at the Statistics and Applied
Mathematical Sciences Institute (SAMSI) in Research Triangle Park in North Carolina …

Large deviation estimates have proved to be the crucial tool required to handle many
questions in statistics, engineering, statistial mechanics, and applied probability. Amir …

We study minimization of the difference of \ell_1 and \ell_2 norms as a nonconvex and
Lipschitz continuous metric for solving constrained and unconstrained compressed sensing …

Simulated annealing and Boltzmann machines: a stochastic approach to combinatorial
optimization and neural computing | Guide books skip to main content ACM Digital Library home …