Picture of person typing on laptop with programming code visible on the laptop screen

World class computing and information science research at Strathclyde...

The Strathprints institutional repository is a digital archive of University of Strathclyde's Open Access research outputs. Strathprints provides access to thousands of Open Access research papers by University of Strathclyde researchers, including by researchers from the Department of Computer & Information Sciences involved in mathematically structured programming, similarity and metric search, computer security, software systems, combinatronics and digital health.

The Department also includes the iSchool Research Group, which performs leading research into socio-technical phenomena and topics such as information retrieval and information seeking behaviour.

Explore

An inflationary differential evolution algorithm for space trajectory optimization

Vasile, Massimiliano and Minisci, Edmondo and Locatelli, Marco (2011) An inflationary differential evolution algorithm for space trajectory optimization. IEEE Transactions on Evolutionary Computation, 15 (2). pp. 267-281. ISSN 1089-778X

[img]
Preview
PDF (An inflationary differential algorithm for space trajectory optimization)
Vasile_M_Pure_An_inflationary_differential_evolution_algorithm_for_space_trajectory_optimization_5_Oct_2010.pdf - Preprint

Download (646kB) | Preview

Abstract

In this paper we define a discrete dynamical system that governs the evolution of a population of agents. From the dynamical system, a variant of Differential Evolution is derived. It is then demonstrated that, under some assumptions on the differential mutation strategy and on the local structure of the objective function, the proposed dynamical system has fixed points towards which it converges with probability one for an infinite number of generations. This property is used to derive an algorithm that performs better than standard Differential Evolution on some space trajectory optimization problems. The novel algorithm is then extended with a guided restart procedure that further increases the performance, reducing the probability of stagnation in deceptive local minima.