A Multi-Objective Evolutionary Algorithm for Shortest Path with Maximal Visual Coverage

Author

Zheng, Changwen ; Yin, Huafei ; Li, Jie ; Lu, Min

Author_Institution

Sci. & Technol. on Integrated Inf. Syst. Lab., Inst. of Software, Beijing, China

fYear

2011

fDate

14-17 Dec. 2011

Firstpage

232

Lastpage

235

Abstract

In this paper, the shortest path planning problem with maximal visual coverage in the raster terrain is studied with the proposal of a multi-objective evolutionary planner. By using a problem-specific representation of candidate solutions and genetic operators, our planner can handle the objectives of the visual coverage and the path length and find the non-dominated solutions efficiently. Utilizing an external archive, our algorithm may effectively obtain the approximate Pareto front with wide distribution to provide multiple candidates for decision-maker.

Keywords

Pareto optimisation; data analysis; decision making; genetic algorithms; geophysical image processing; image representation; path planning; terrain mapping; Pareto front approximation; decision maker; genetic operator; maximal visual coverage; multiobjective evolutionary algorithm; nondominated solution; problem-specific representation; shortest path planning problem; Algorithm design and analysis; Approximation algorithms; Biological cells; Evolutionary computation; Path planning; Shortest path problem; Visualization; Evolutionary Algorithm; Multi-Objective Optimization; Pareto Front; Shortest Path; Visual Coverage;

fLanguage

English

Publisher

ieee

Conference_Titel

Intelligent Computation and Bio-Medical Instrumentation (ICBMI), 2011 International Conference on

Conference_Location

Wuhan, Hubei

Print_ISBN

978-1-4577-1152-7

Type

conf

DOI

10.1109/ICBMI.2011.30

Filename

6131779