## Evolutionary Algorithms for Solving Multi-Objective ProblemsSolving multi-objective problems is an evolving effort, and computer science and other related disciplines have given rise to many powerful deterministic and stochastic techniques for addressing these large-dimensional optimization problems. Evolutionary algorithms are one such generic stochastic approach that has proven to be successful and widely applicable in solving both single-objective and multi-objective problems. This textbook is a second edition of Evolutionary Algorithms for Solving Multi-Objective Problems, significantly expanded and adapted for the classroom. The various features of multi-objective evolutionary algorithms are presented here in an innovative and student-friendly fashion, incorporating state-of-the-art research. The book disseminates the application of evolutionary algorithm techniques to a variety of practical problems, including test suites with associated performance based on a variety of appropriate metrics, as well as serial and parallel algorithm implementations. |

### What people are saying - Write a review

mopso

### Contents

XLIII | 284 |

XLIV | 300 |

XLV | 333 |

XLVI | 334 |

XLVII | 339 |

XLVIII | 340 |

XLIX | 388 |

L | 407 |

IX | 55 |

X | 57 |

XI | 61 |

XII | 63 |

XIII | 88 |

XIV | 113 |

XV | 116 |

XVI | 120 |

XVII | 121 |

XVIII | 122 |

XIX | 131 |

XX | 144 |

XXI | 147 |

XXII | 152 |

XXIII | 165 |

XXIV | 168 |

XXV | 171 |

XXVI | 175 |

XXVII | 176 |

XXVIII | 179 |

XXIX | 199 |

XXX | 220 |

XXXI | 222 |

XXXII | 228 |

XXXIII | 229 |

XXXIV | 233 |

XXXV | 235 |

XXXVI | 236 |

XXXVII | 243 |

XXXVIII | 268 |

XXXIX | 273 |

XL | 276 |

XLI | 277 |

XLII | 283 |