The random step maneuver with uniformly distributed starting times has the disadvantage that it cannot focus the starting time on the more efficiency time. It decreases the penetration probability. To resolve this pro...The random step maneuver with uniformly distributed starting times has the disadvantage that it cannot focus the starting time on the more efficiency time. It decreases the penetration probability. To resolve this problem, a random step penetration algorithm with normal distribution starting time is proposed. Using the shaping filters and adjoint system method, the miss distance with different starting times can be acquired. According to the penetration standard, the time window ensuring successful penetration can be calculated and it is used as the 3σ bound of the normally distributed random maneuver. Simulation results indicate that the normally distributed random maneuver has higher penetration probability than the uniformly distributed random maneuver.展开更多
Cuckoo search （CS）, inspired by the obligate brood parasitic behavior of some cuckoo species, iteratively uses L6vy flights random walk （LFRW） and biased/selective random walk （BSRW） to search for new solutions....Cuckoo search （CS）, inspired by the obligate brood parasitic behavior of some cuckoo species, iteratively uses L6vy flights random walk （LFRW） and biased/selective random walk （BSRW） to search for new solutions. In this study, we seek a simple strategy to set the scaling factor in LFRW, which can vary the scaling factor to achieve better performance. However, choosing the best scaling factor for each problem is intractable. Thus, we propose a varied scal- ing factor （VSF） strategy that samples a value from the range [0,1] uniformly at random for each iteration. In addition, we integrate the VSF strategy into several advanced CS vari- ants. Extensive experiments are conducted on three groups of benchmark functions including 18 common test functions, 25 functions proposed in CEC 2005, and 28 functions intro- duced in CEC 2013. Experimental results demonstrate the ef- fectiveness of the VSF strategy.展开更多
文摘The random step maneuver with uniformly distributed starting times has the disadvantage that it cannot focus the starting time on the more efficiency time. It decreases the penetration probability. To resolve this problem, a random step penetration algorithm with normal distribution starting time is proposed. Using the shaping filters and adjoint system method, the miss distance with different starting times can be acquired. According to the penetration standard, the time window ensuring successful penetration can be calculated and it is used as the 3σ bound of the normally distributed random maneuver. Simulation results indicate that the normally distributed random maneuver has higher penetration probability than the uniformly distributed random maneuver.
文摘Cuckoo search （CS）, inspired by the obligate brood parasitic behavior of some cuckoo species, iteratively uses L6vy flights random walk （LFRW） and biased/selective random walk （BSRW） to search for new solutions. In this study, we seek a simple strategy to set the scaling factor in LFRW, which can vary the scaling factor to achieve better performance. However, choosing the best scaling factor for each problem is intractable. Thus, we propose a varied scal- ing factor （VSF） strategy that samples a value from the range [0,1] uniformly at random for each iteration. In addition, we integrate the VSF strategy into several advanced CS vari- ants. Extensive experiments are conducted on three groups of benchmark functions including 18 common test functions, 25 functions proposed in CEC 2005, and 28 functions intro- duced in CEC 2013. Experimental results demonstrate the ef- fectiveness of the VSF strategy.
