TY - JOUR
T1 - Research on vehicle assignment model for constraints handling based on computational intelligence algorithms
AU - Pan, Feng
AU - Chen, Jie
AU - Ren, Zhi Ping
AU - Wang, Guang Hui
PY - 2009/12
Y1 - 2009/12
N2 - The task allocation of unmanned aerial vehicle (UAV) is a complex assignment problem with various constraints. With the increase of the size of scenarios and the number of constraints, UAV assignment problems become more complicated. Especially, the potential dimensional explosion and optimization difficulty are unavoidable to those algorithms based on linear programming. A new UAV assignment model was proposed, which transforms the UAV assignment problem into a multi-constraint optimization problem. The proposed model reduces the dimension of solution space effectively, improves the optimization efficiency, and is adapted to the other computational intelligence algorithms. Several computational intelligence algorithms, such as particle swarm optimization, genetic algorithm, differential evolution algorithm, clonal selection algorithm, were applied to accomplish the optimization work. Numerical experimented results illustrate that the model has better adaptability and extensibility, can solve complex UAV assignment problems combined with the computational intelligence algorithms.
AB - The task allocation of unmanned aerial vehicle (UAV) is a complex assignment problem with various constraints. With the increase of the size of scenarios and the number of constraints, UAV assignment problems become more complicated. Especially, the potential dimensional explosion and optimization difficulty are unavoidable to those algorithms based on linear programming. A new UAV assignment model was proposed, which transforms the UAV assignment problem into a multi-constraint optimization problem. The proposed model reduces the dimension of solution space effectively, improves the optimization efficiency, and is adapted to the other computational intelligence algorithms. Several computational intelligence algorithms, such as particle swarm optimization, genetic algorithm, differential evolution algorithm, clonal selection algorithm, were applied to accomplish the optimization work. Numerical experimented results illustrate that the model has better adaptability and extensibility, can solve complex UAV assignment problems combined with the computational intelligence algorithms.
KW - Clonal selection algorithm
KW - Differential evolution algorithm
KW - Genetic algorithm
KW - Operational research
KW - Particle swarm optimization
KW - Unmanned aerial vehicle assignment problem
UR - http://www.scopus.com/inward/record.url?scp=75849137940&partnerID=8YFLogxK
M3 - Article
AN - SCOPUS:75849137940
SN - 1000-1093
VL - 30
SP - 1706
EP - 1713
JO - Binggong Xuebao/Acta Armamentarii
JF - Binggong Xuebao/Acta Armamentarii
IS - 12
ER -