Metaheuristic algorithms are computational intelligence paradigms especially used for
sophisticated solving optimization problems. This chapter aims to review of all …

The next-generation of pavement maintenance and rehabilitation (M&R) decision-making
needs to weigh multiple strategic goals to achieve sustainable development through the …

Genetic Algorithms are heuristic search approaches that are applicable to a wide range of
optimization problems. This flexibility makes them attractive for many optimization problems …

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

This is the second edition of our 2003 book. It is primarily a book for lecturers and graduate
and undergraduate students. To this group the book offers a thorough introduction to …

Featuring copious introductory material by distinguished scientist Dr. David B. Fogel, this
formidable collection of 30 landmark papers spans the entire history of evolutionary …

Providing an up-to-date overview of the most popular global optimization methods used in
interpreting geophysical observations, this new edition includes a detailed description of the …

This paper analyzes the convergence properties of the canonical genetic algorithm (CGA)
with mutation, crossover and proportional reproduction applied to static optimization …

Proceedings of the Genetic and Evolutionary Computation Conference Companion:
Evolutionary computation: a unified approach Page 1 1 Evolutionary Computation: A …

Natural evolution is a population-based optimization process. Simulating this process on a
computer results in stochastic optimization techniques that can often outperform classical …