UAV Cooperative Task Assignments for a SEAD Mission Using Genetic Algorithms

AIAA Guidance, Navigation, and Control Conference and Exhibit ◽

10.2514/6.2006-6456 ◽

2006 ◽

Cited By ~ 16

Author(s):

Marjorie Darrah ◽

William Niland ◽

Brian Stolarik ◽

Lance Walp

Keyword(s):

Genetic Algorithms ◽

Task Assignments

Download Full-text

Genetic algorithms for task assignments in logistic warehouses

International Journal of Modelling in Operations Management ◽

10.1504/ijmom.2019.10024604 ◽

2019 ◽

Vol 7 (3) ◽

pp. 196

Author(s):

Min Wang ◽

Zhaodong Wu

Keyword(s):

Genetic Algorithms ◽

Task Assignments

Download Full-text

Genetic algorithms for task assignments in logistic warehouses

International Journal of Modelling in Operations Management ◽

10.1504/ijmom.2019.103036 ◽

2019 ◽

Vol 7 (3) ◽

pp. 196

Author(s):

Zhaodong Wu ◽

Min Wang

Keyword(s):

Genetic Algorithms ◽

Task Assignments

Download Full-text

Multiple task assignments for cooperating uninhabited aerial vehicles using genetic algorithms

Computers & Operations Research ◽

10.1016/j.cor.2005.02.039 ◽

2006 ◽

Vol 33 (11) ◽

pp. 3252-3269 ◽

Cited By ~ 158

Author(s):

Tal Shima ◽

Steven J. Rasmussen ◽

Andrew G. Sparks ◽

Kevin M. Passino

Keyword(s):

Genetic Algorithms ◽

Aerial Vehicles ◽

Uninhabited Aerial Vehicles ◽

Multiple Task ◽

Task Assignments

Download Full-text

UAV cooperative multiple task assignments using genetic algorithms

Proceedings of the 2005, American Control Conference, 2005. ◽

10.1109/acc.2005.1470429 ◽

2005 ◽

Cited By ~ 10

Author(s):

Tal Shima ◽

S.J. Rasmussen ◽

A.G. Sparks

Keyword(s):

Genetic Algorithms ◽

Multiple Task ◽

Task Assignments

Download Full-text

Hierarchical time-optimal control of a continuous copolymerization reactor during start-up or grade change operation using genetic algorithms

Computers & Chemical Engineering ◽

10.1016/s0098-1354(97)00186-5 ◽

1997 ◽

Vol 21 (1-2) ◽

pp. S1037-S1042

Author(s):

H Moo

Keyword(s):

Optimal Control ◽

Genetic Algorithms ◽

Time Optimal Control ◽

Grade Change ◽

Start Up ◽

Time Optimal ◽

Change Operation ◽

Grade Change Operation

Download Full-text

Genetic Algorithms—a Tool for OR?

Journal of the Operational Research Society ◽

10.1057/palgrave.jors.0470406 ◽

1996 ◽

Vol 47 (4) ◽

pp. 550-561 ◽

Cited By ~ 2

Author(s):

Kathryn A Dowsland

Keyword(s):

Genetic Algorithms

Download Full-text

Road Horizontal Alignment Design Method for Continuous Loop Area in Autonomous Vehicles Proving Ground Based on Genetic Algorithms

CICTP 2020 ◽

10.1061/9780784483053.163 ◽

2020 ◽

Author(s):

Junyi Chen ◽

Rubing Li ◽

Xingyu Xing ◽

Lu Xiong

Keyword(s):

Genetic Algorithms ◽

Autonomous Vehicles ◽

Design Method ◽

Horizontal Alignment ◽

Loop Area

Download Full-text

Enhanced Artificial Intelligent Method for Representing the Photonic Crystal Fiber Profile Index

Al-Kitab Journal for Pure Sciences ◽

10.32441/kjps.v1i1.87 ◽

2018 ◽

Vol 1 (1) ◽

pp. 2-19

Author(s):

Mahmood Sh. Majeed ◽

Raid W. Daoud

Keyword(s):

Genetic Algorithms ◽

Photonic Crystal ◽

Photonic Crystal Fiber ◽

New Method ◽

Proper Solution ◽

Artificial Intelligent ◽

Crystal Fiber ◽

Fitness Value ◽

First Pass ◽

Crossover And Mutation

A new method proposed in this paper to compute the fitness in Genetic Algorithms (GAs). In this new method the number of regions, which assigned for the population, divides the time. The fitness computation here differ from the previous methods, by compute it for each portion of the population as first pass, then the second pass begin to compute the fitness for population that lye in the portion which have bigger fitness value. The crossover and mutation and other GAs operator will do its work only for biggest fitness portion of the population. In this method, we can get a suitable and accurate group of proper solution for indexed profile of the photonic crystal fiber (PCF).

Download Full-text