Paper Info
Title
Multi-objective optimization for selecting and scheduling observations by agile earth observing satellites
Abstract
This paper presents a biased random-key genetic algorithm for solving a multi-objective optimization problem concerning the management of agile Earth observing satellites. It addresses the selection and scheduling of a subset of photographs from a set of candidates in order to optimize two objectives: maximizing the total profit, and ensuring fairness among users by minimizing the maximum profit difference between users. Two methods, one based on dominance, the other based on indicator, are compared to select the preferred solutions. The methods are evaluated on realistic instances derived from the 2003 ROADEF challenge.
Year
DOI
Venue
2012
10.1007/978-3-642-32964-7_12
PPSN (2)
Keywords
Field
DocType
multi-objective optimization problem,agile earth,multi-objective optimization,scheduling observation,preferred solution,maximum profit difference,random-key genetic algorithm,roadef challenge,realistic instance,total profit
Mathematical optimization,Satellite,Computer science,Scheduling (computing),Multi-objective optimization,Agile software development,Optimization problem,Genetic algorithm
Conference
Citations 
PageRank 
References 
8
0.56
6
Authors
3
Name
Order
Citations
PageRank
Panwadee Tangpattanakul1261.91
Nicolas Jozefowiez234821.58
Pierre Lopez3241.92