Cooperative co-evolution has been introduced into evolutionary algorithms with the aim of
solving increasingly complex optimization problems through a divide-and-conquer …

We are delighted that SIAM is republishing our original 1983 book after what many in the
optimization field have regarded as “premature termination” by the previous publisher. At 12 …

One of the most effective methods for nonlinearly constrained optimization generates steps
by solving quadratic subproblems. This sequential quadratic programming (SQP) approach …

We study the numerical performance of a limited memory quasi-Newton method for large
scale optimization, which we call the L-BFGS method. We compare its performance with that …

This report proposes 15 large-scale benchmark problems as an extension to the existing
CEC'2010 large-scale global optimization benchmark suite. The aim is to better represent a …

This book on iterative methods for linear and nonlinear equations can be used as a tutorial
and a reference by anyone who needs to solve nonlinear systems of equations or large …

This book on unconstrained and bound constrained optimization can be used as a tutorial
for self-study or a reference by those who solve such problems in their work. It can also …

This is a book for people interested in solving optimization problems. Because of the wide
(and growing) use of optimization in science, engineering, economics, and industry, it is …

Publisher Summary This chapter discusses the most basic nonlinear optimization problem in
continuous variables, the unconstrained optimization problem. The basic methods for …

In the past decades, different kinds of metaheuristic optimization algorithms [1, 2] have been
developed; Simulated Annealing (SA)[3, 4], Evolutionary Algorithms (EAs)[5–7], Differential …