Title :
An anytime algorithm based on modified GA for dynamic weapon-target allocation problem
Author :
Wu, Ling ; Wang, Hang-yu ; Lu, Fa-xing ; Jia, Peifa
Author_Institution :
Tsinghua Univ., Beijing
Abstract :
An anytime algorithm based on modified genetic algorithm (GA) for dynamic WTA problem, subject to temporal constraints, is developed in the paper. In the algorithm the weapons are assigned to targets one by one before the deadline of each target comes. After a target is assigned with some weapon, the target is replaced by a new one in all chromosomes in the population while the optimization process will not undergo any restart. The algorithm has three main advantages: 1) a new target can be dynamically accommodated in the allocation process without losing previous optimizing information, 2) the quality of the pairing decisions may be improved in the evolving process with a prolonged computation time, and 3) it optimally deploys weapons to targets where a weapon can be assigned to more than one target asynchronously without missing any deadline of the targets, under the precondition that the weapon can be allocated to only one target at one time. The feasibility and the validity of the modified GA are verified in simulations.
Keywords :
genetic algorithms; weapons; allocation process; anytime algorithm; dynamic weapon-target allocation problem; genetic algorithm; optimization process; temporal constraints; weapons; Evolutionary computation; Weapons;
Conference_Titel :
Evolutionary Computation, 2008. CEC 2008. (IEEE World Congress on Computational Intelligence). IEEE Congress on
Conference_Location :
Hong Kong
Print_ISBN :
978-1-4244-1822-0
Electronic_ISBN :
978-1-4244-1823-7
DOI :
10.1109/CEC.2008.4631065