Title :
Solving the multi-objective quadratic assignment problem using a fast messy genetic algorithm
Author :
Day, Richard O. ; Kleeman, Mark P. ; Lamont, Gary B.
Author_Institution :
Dept. of Electr. & Comput. Eng., Air Force Inst. of Technol., Wright-Patterson AFB, OH, USA
Abstract :
The multiobjective quadratic assignment problem is an NP-complete problem with a multitude of real-world applications. The specific application addressed is the minimization of communication flows in a heterogenous mix of unmanned aerial vehicles. Developed is a multiobjective approach to solving the general mQAP for this UAV application. The combinatoric nature of this problem calls for a stochastic search algorithm; moreover, the multiobjective fast messy genetic algorithm (MOMGA-II) [Jesse Zydallis (2003)] is used for experimentation. Results indicate that much of the Pareto optimal points are found.
Keywords :
Pareto optimisation; genetic algorithms; minimisation; operations research; quadratic programming; remotely operated vehicles; stochastic programming; NP-complete problem; Pareto optimal points; communication flow minimization; fast messy genetic algorithm; multiobjective quadratic assignment problem; real-world applications; stochastic search algorithm; unmanned aerial vehicles; Aircraft; Application software; Combinatorial mathematics; Computer hacking; Evolutionary computation; Genetic algorithms; NP-complete problem; Protection; Reconnaissance; Unmanned aerial vehicles;
Conference_Titel :
Evolutionary Computation, 2003. CEC '03. The 2003 Congress on
Print_ISBN :
0-7803-7804-0
DOI :
10.1109/CEC.2003.1299372
