DocumentCode :
1350101
Title :
A Process Algebra Genetic Algorithm
Author :
Karaman, Sertac ; Shima, Tal ; Frazzoli, Emilio
Author_Institution :
Dept. of Electr. Eng. & Comput. Sci., Massachusetts Inst. of Technol., Cambridge, MA, USA
Volume :
16
Issue :
4
fYear :
2012
Firstpage :
489
Lastpage :
503
Abstract :
A genetic algorithm that utilizes process algebra for coding of solution chromosomes and for defining evolutionary based operators is presented. The algorithm is applicable to mission planning and optimization problems. As an example the high level mission planning for a cooperative group of uninhabited aerial vehicles is investigated. The mission planning problem is cast as an assignment problem, and solutions to the assignment problem are given in the form of chromosomes that are manipulated by evolutionary operators. The evolutionary operators of crossover and mutation are formally defined using the process algebra methodology, along with specific algorithms needed for their execution. The viability of the approach is investigated using simulations and the effectiveness of the algorithm is shown in small, medium, and large scale problems.
Keywords :
autonomous aerial vehicles; genetic algorithms; process algebra; assignment problem; chromosomes; crossover; evolutionary based operators; high level mission planning; mission planning; optimization problems; process algebra genetic algorithm; uninhabited aerial vehicles; Algebra; Genetic algorithms; Routing; Schedules; Semantics; Vehicles; Genetic algorithms; UAV task assignment; process algebra;
fLanguage :
English
Journal_Title :
Evolutionary Computation, IEEE Transactions on
Publisher :
ieee
ISSN :
1089-778X
Type :
jour
DOI :
10.1109/TEVC.2011.2160400
Filename :
6045330
Link To Document :
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