This book examines the problem of maintenance planning and scheduling in industrial production systems. It presents two practically relevant, deterministic mathematical models: the capacitated planned
The meta-heuristic hybrid optimization techniques discussed in this collection address the intrinsic difficulty of algorithms and the need to model uncertainty problems troubling modern industrial, bu
Artificial neural networks, genetic algorithms and the ant colony optimization algorithm have become a highly effective tool for solving hard optimization problems. As their popularity has increased,
Covers developments in bilinear systems theory Focuses on the control of open physical processes functioning in a non-equilibrium mode Emphasis is on three primary disciplines: modern differential geo
This book presents the latest findings on stochastic dynamic programming models and on solving optimal control problems in networks. It includes the authors’ new findings on determining the optimal so
This book presents basic optimization principles and gradient-based algorithms to a general audience, in a brief and easy-to-read form. It enables professionals to apply optimization theory to enginee
This textbook provides a comprehensive introduction to nature-inspired metaheuristic methods for search and optimization, including the latest trends in evolutionary algorithms and other forms of natu
This book covers the design and optimization of computer networks applying a rigorous optimization methodology, applicable to any network technology. It is organized into two parts. In Part 1 th
?This book aims at illustrating strategies to account for uncertainty in complex systems described by computer simulations. When optimizing the performances of these systems, accounting or neglecting
This work consists of 12 chapters by international researchers and practitioners in computer science and software engineering. The book opens with a survey of applications of evolutionary and bio-insp
While the weight of a structure constitutes a significant part of the cost, a minimum weight design is not necessarily the minimum cost design. Little attention in structural optimization has been pai
Manufacturing systems, regardless of their size, have to work with scarce resources in dynamic environments. Managers are asked to assign production facilities over time to parallel activities respec
Iterative Computer Algorithms with Applications in Engineering describes in-depth the five main iterative algorithms for solving hard combinatorial optimization problems: Simulated Annealing, Genetic
The study of discrete structures and networks becomes more and more important in decision theory. A relevant topic in modern control theory reflecting this fact is concerned with multiobjective contro
Due to its inherent time-scale locality characteristics, the discrete wavelet transform (DWT) has received considerable attention in signal/image processing. Wavelet transforms have excellent energy c
This book covers the theory, history, mathematics, and applications of evolutionary optimization algorithms. Most of these algorithms are motivated by biological processes. The algorithms that are dis
The focus of the present volume is stochastic optimization of dynamical systems in discrete time where - by concentrating on the role of information regarding optimization problems - it discusses the
In this book, a methodology for parameter adaptation in meta-heuristic op-timization methods is proposed. This methodology is based on using met-rics about the population of the meta-heuristic methods
