arrow
Return

A Process Algebra Genetic Algorithm

delete2012-08-01
delete15
delete
OA
AI
S
Sertaç Karaman *
T
Tal Shima
E
Emilio Frazzoli
DOI:10.1109/TEVC.2011.2160400delete
deleteOriginal
deleteShare
deleteSave
View PDF
Abstract

Abstract

En 中文
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:
Genetic algorithms
process algebra
UAV task assignment
AI Summary

AI Summary

Key information extracted from the uploaded paper, including a brief overview, abstract, background, key highlights, visual analysis, and future outlook.

Journal

IEEE Transactions on Evolutionary Computation cover
IEEE Transactions on Evolutionary Computation
IF:
12
Papers:
1.8K
Citations:
2.4W

Organization

T
Technion Israel Institute of Technology
Scholars:
1.6W
Papers: 1.5W
Citations: 2.0W