Title :
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
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;
Conference_Titel :
Intelligent Computation and Bio-Medical Instrumentation (ICBMI), 2011 International Conference on
Conference_Location :
Wuhan, Hubei
Print_ISBN :
978-1-4577-1152-7
DOI :
10.1109/ICBMI.2011.30
