@inbook{19d9940a8470404aba70d4e445cda52c,
title = "Hybrid behavioural-based multi-objective space trajectory optimization",
abstract = "In this chapter we present a hybridization of a stochastic based search approach for multi-objective optimization with a deterministic domain decomposition of the solution space. Prior to the presentation of the algorithm we introduce a general formulation of the optimization problem that is suitable to describe both single and multi-objective problems. The stochastic approach, based on behaviorism, combinedwith the decomposition of the solutions pace was tested on a set of standard multi-objective optimization problems and on a simple but representative case of space trajectory design.",
keywords = "global optimization, genetic algorithm, space trajectory design, multi-objective optimization",
author = "Massimiliano Vasile",
year = "2009",
doi = "10.1007/978-3-540-88051-6",
language = "English",
isbn = "978-3-540-88050-9",
volume = "171",
series = "Studies in Computational Intelligence",
publisher = "Springer Berlin Heidelberg",
pages = "231--253",
booktitle = "Multi-Objective Memetic Algorithms",
}