A genetic algorithm for shortest path motion problem in three dimensions

Marzio Pennisi, Francesco Pappalardo, Alfredo Motta, Alessandro Cincotti

Risultato della ricerca: Capitolo in libro/report/atti di convegnoContributo a conferenzapeer review

Abstract

We present an evolutionary approach to search for nearoptimal solutions for the shortest path motion problem in three dimensions (between a starting and an ending point) in the presence of obstacles. The proposed genetic algorithm makes use of newly defined concepts of crossover and mutation and effective, problem optimized, methods for candidate solution generation. We test the performances of the algorithm on several test cases.

Lingua originaleInglese
Titolo della pubblicazione ospiteAdvanced Intelligent Computing Theories and Applications
Sottotitolo della pubblicazione ospiteWith Aspects of Artificial Intelligence - Third International Conference on Intelligent Computing, ICIC 2007, Proceedings
EditoreSpringer Verlag
Pagine534-542
Numero di pagine9
ISBN (stampa)9783540742012
DOI
Stato di pubblicazionePubblicato - 2007
Pubblicato esternamente
Evento3rd International Conference on Intelligent Computing, ICIC 2007 - Qingdao, China
Durata: 21 ago 200724 ago 2007

Serie di pubblicazioni

NomeLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume4682 LNAI
ISSN (stampa)0302-9743
ISSN (elettronico)1611-3349

???event.eventtypes.event.conference???

???event.eventtypes.event.conference???3rd International Conference on Intelligent Computing, ICIC 2007
Paese/TerritorioChina
CittàQingdao
Periodo21/08/0724/08/07

Fingerprint

Entra nei temi di ricerca di 'A genetic algorithm for shortest path motion problem in three dimensions'. Insieme formano una fingerprint unica.

Cita questo