The field of global optimization has been developing at a rapid pace. There is a journal
devoted to the topic, as well as many publications and notable books discussing various …

Grover's quantum computational search procedure can provide the basis for implementing
adaptive global optimization algorithms. A brief overview of the procedure is given and a …

Random search algorithms are very useful for simulation optimization, because they are
relatively easy to implement and typically find a “good” solution quickly. One drawback is …

Backtracking adaptive search is a simplified stochastic optimisation procedure which permits
the acceptance of worsening objective function values. Key properties of backtracking …

Backtracking adaptive search is an optimisation algorithm which generalises pure adaptive
search and hesitant adaptive search. This paper considers the number of iterations for which …

Machine learning is a branch of Artificial Intelligence that seeks to make machines learn
from data. It is being applied for solving real world problems with huge amount of data …

Quantum computers are designed based on quantum mechanics. They have special
features such as entanglement and parallelism, which do not exist in classic mechanics …

Laboratório Nacional de Computaçao Cientıfica Programa de Pós Graduaçao em Modelagem
Computacional Otimizaçao de F Page 1 Laboratório Nacional de Computaçao Cientıfica …

Objective functions, stochastic algorithms and convergence rates Page 1 Objective functions,
stochastic algorithms and convergence rates M. Locatelli and GR Wood 1 Introduction The …

Additions to the Stochastic Programming Bibliography Page 1 Additions to the Stochastic
Programming Bibliography Maarten H. van der Vlerk Department Operations University of …