Open AccessBook
Nature-Inspired Algorithms for Optimisation
Raymond Chiong
- 01 Jan 2009
TL;DR: This volume is a collection of the latest state-of-the-art algorithms and important studies for tackling various kinds of optimisation problems, and the contributions stand out through their novelty and clarity of the algorithmic descriptions and analyses.
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Abstract: Nature-Inspired Algorithms are gaining much popularity in recent years due to the fact that many real-world optimisation problems have become increasingly large, complex and dynamic. The size and complexity of the problems nowadays require the development of methods and solutions whose efficiency is measured by their ability to find acceptable results within a reasonable amount of time, rather than an ability to guarantee the optimal solution. This volume "Nature-Inspired Algorithms for Optimisation" is a collection of the latest state-of-the-art algorithms and important studies for tackling various kinds of optimisation problems. It comprises 18 chapters, including two introductory chapters which address the fundamental issues that have made optimisation problems difficult to solve and explain the rationale for seeking inspiration from nature. The contributions stand out through their novelty and clarity of the algorithmic descriptions and analyses, and lead the way to interesting and varied new applications.
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Citations
jMetal: A Java framework for multi-objective optimization
Juan J. Durillo,Antonio J. Nebro +1 more
TL;DR: This paper describes jMetal, an object-oriented Java-based framework aimed at the development, experimentation, and study of metaheuristics for solving multi-objective optimization problems, and includes two case studies to illustrate the use of jMetal in both solving a problem with a metaheuristic and designing and performing an experimental study.
1.1K
Memetic algorithms and memetic computing optimization: A literature review
Ferrante Neri,Carlos Cotta +1 more
TL;DR: Several classes of optimization problems, such as discrete, continuous, constrained, multi-objective and characterized by uncertainties, are addressed by indicating the memetic “recipes” proposed in the literature.
647
Survey paper: A survey on industrial applications of fuzzy control
TL;DR: A survey on recent developments of analysis and design of fuzzy control systems focused on industrial applications reported after 2000 is presented.
551
Metaheuristics in large-scale global continues optimization
TL;DR: The paper mainly covers the fundamental algorithmic frameworks such as decomposition and non-decomposition methods, and their current applications in the field of large-scale global optimization.
464
Bi-goal evolution for many-objective optimization problems
TL;DR: The proposed approach, BiGE, is the first step towards a new way of addressing many-objective problems as well as indicating several important issues for future development of this type of algorithms.
233
References
Improved Particle Swarm Optimization in Constrained Numerical Search Spaces
Efrén Mezura-Montes,Jorge Isacc Flores-Mendoza +1 more
- 01 Jan 2009
TL;DR: The Improved PSO (IPSO) is extensively compared against the original PSO variants, based on the quality and consistency of the final results and also on two performance measures and convergence graphs to analyze their on-line behavior.
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