TY - GEN
T1 - A genetic algorithm for shortest path motion problem in three dimensions
AU - Pennisi, Marzio
AU - Pappalardo, Francesco
AU - Motta, Alfredo
AU - Cincotti, Alessandro
PY - 2007
Y1 - 2007
N2 - 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.
AB - 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.
UR - https://www.scopus.com/pages/publications/38049016481
U2 - 10.1007/978-3-540-74205-0_58
DO - 10.1007/978-3-540-74205-0_58
M3 - Conference contribution
AN - SCOPUS:38049016481
SN - 9783540742012
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 534
EP - 542
BT - Advanced Intelligent Computing Theories and Applications
PB - Springer Verlag
T2 - 3rd International Conference on Intelligent Computing, ICIC 2007
Y2 - 21 August 2007 through 24 August 2007
ER -