Multi-Objective Optimization Using Evolutionary Algorithms
Evolutionary algorithms are relatively new, but very powerfultechniques used to find solutions to many real-world search andoptimization problems. Many of these problems have multipleobjectives, which leads to the need to obtain a set of optimalsolutions, known as effective solutions. It has been found thatusing evolutionary algorithms is a highly effective way of findingmultiple effective solutions in a single simulation run.
The integrated presentation of theory, algorithms and exampleswill benefit those working and researching in the areas ofoptimization, optimal design and evolutionary computing. This textprovides an excellent introduction to the use of evolutionaryalgorithms in multi-objective optimization, allowing use as agraduate course text or for self-study.
NonElitist MultiObjective Evolutionary Algorithms
Elitist MultiObjective Evolutionary Algorithms
Constrained MultiObjective Evolutionary Algorithms