Genetic Algorithms

ICMAT 2011 Singapore: Final Session – Sensing / Probes

Paul Stewart
Symposium Chair Prof Dave Fernig of the University of Liverpool closing the Symposium

Thursday 1st July was the final day of the Fontiers in Optical Bio-Imaging and Microscopy Symposium

AA8-1 (Invited Talk)

Looking for Clues – Solving Complex Problems with Biologically Inspired Heuristics

Paul Stewart and Jun Chen (University of Lincoln), David Fernig (University of Liverpool), Laurence Duchesne (Universite Pierre et Marie Curie, France)

AA8-5

New Probes for Imaging: Ligand Shells for Nanoparticles

David Fernig (University of Liverpool), Laurence Duchesne (Universite Pierre et Marie Curie, France)

Martin Lear, National University of Singapore presents 'Fluorescent Labelling of Drugs and Natural Products'

Finally Colin Dowding closed our participation in the conference today by presenting:

J12.2-1

Topography of Features Machined into Bisphenol A Polycarbonate Using Closed Thick Film Flowing Filtered Water Immersed KrF Excimer Laser Ablation

Colin Dowding, Jonathan Lawrence and Paul Stewart (University of Lincoln.

in the Nanoscale Characterization session

Paper presentation timetable for ICMAT 2011, Singapore

Paul Stewart

International Conference on Materials for Advanced Technologies 26 June – 1 July 2011, SUNTEC, Singapore

Session Code J12.2 – Nanoscale Characterization

Session Chair(s) Jinchong Xiao Paper Details: J12.2-1
Topography of Features Machined Into Bisphenol A Polycarbonate Using Closed Thick Film Flowing Filtered Water Immersed KrF Excimer Laser Ablation
Colin DOWDING1, Jonathan LAWRENCE1, Paul STEWART2#+
1Faculty of Engineering, University of Lincoln, United Kingdom,

2School of Engineering, University of Lincoln, United Kingdom

Presentation Mode: Oral Date/Time Slot: Fri – 1 Jul 11 / 14:00 – 16:00 Presentation Room: 309 Presentation Length: 15 minutes Presentation Order: 1st in the timeslot

Session Code AA8 – Sensing / Probes

Session Chair(s) Vladimir Korzh Paper Details: AA8-2 (Invited)
Looking for Clues – Solving Complex Problems with Biologically Inspired Heuristics
Paul STEWART1#+, Jun CHEN1, David FERNIG2
1School of Engineering, University of Lincoln, United Kingdom,

2University of Liverpool, United Kingdom

Presentation Mode: Oral Date/Time Slot: Thu – 30 Jun 11 / 16:30 – 18:00 Presentation Room: 320 Presentation Length: 30 minutes Presentation Order: 2nd in the timeslot

Session Code AA3 – Photothermal Microscopy

Session Chair(s) Guo Hong Chen

Paper Details: AA3-2 Heparan Sulfate Determines the Modes of Diffusion of Fibroblast Growth Factor2 within the Pericellular Matrix

Laurence DUCHESNE1, Vivien OCTEAU2, Rachel BEARON3, Paul STEWART4, Jun CHEN5, Ian PRIOR6, Alison BECKETT6, Brahim LOUNIS2, David FERNIG7#+

1Institut du Fer à Moulin, UMR-S 839 INSERM, University Pierre and Marie Curie, France,

2University of Bordeaux, France,

3Mathematical Sciences, University of Liverpool, United Kingdom,

4School of Engineering, University of Lincoln, United Kingdom,

5Department of Engineering, University of Lincoln, United Kingdom,

6Physiological Laboratory, University of Liverpool, United Kingdom,

7Structural and Chemical biology, University of Liverpool, United Kingdom

Presentation Mode: Oral Date/Time Slot: Mon – 27 Jun 11 / 16:30 – 18:00 Presentation Room:  320  Presentation Length: 15 minutes Presentation Order: 2nd in the timeslot

Best paper prize for School of Engineering academics

Paul Stewart
Institution of Mechanical Engineers headquarters London

Prof Paul Stewart and Dr Jill Stewart from the School of Engineering in collaboration with Dr Dan Gladwin from the University of Sheffield have been awarded the Charles Sharpe Beecher Prize by the Institution of Mechanical Engineers for their 2010 paper

Multi-objective evolutionary–fuzzy augmented flight control for an F16 aircraft. Proceedings of the IMechE, Part G: Journal of Aerospace Engineering, 224 (3). pp. 293-309. ISSN 0954-4100

The prize is awarded for the best paper on an aerospace subject published by the Institution in the previous year.

The paper examines the application of Artificial Intelligence techniques to the flight control system of the Lockheed Martin F16 Fighting Falcon. In particular, the modified controller aims to enhance the performance of the flight controller to reduce pilot fatigue during extended combat flight manoeuvres.

The F-16 is a single-engined, supersonic, multi-role tactical aircraft. The F-16 was designed to be a cost-effective combat “workhorse” that can perform various kinds of missions and maintain around-the-clock readiness. It is much smaller and lighter than its predecessors, but uses advanced aerodynamics and avionics, including the first use of a relaxed static stability/fly-by-wire (RSS/FBW) flight control system, to achieve enhanced maneuver performance. Highly nimble, the F-16 can pull 9-g maneuvers and can reach a maximum speed of over Mach 2.

The Prize will be awarded at the Annual General Meeting and Awards Ceremony at the IMechE London headquarters on 17th May 2011

A controlled migration genetic algorithm operator for hardware-in-the-loop experimentation

Paul Stewart

Lotus free-piston experimental engine

A controlled migration genetic algorithm operator for hardware-in-the-loop experimentation

D. Gladwina, P. Stewartb, , and J. Stewartb

a Department of Electronic and Electrical Engineering, University of Sheffield, Mappin St. Sheffield S1 3JD, UK

b School of Engineering, University of Lincoln, Lincoln LN6 7TS, UK

Engineering Applications of Artificial Intelligence
Volume 24, Issue 4, June 2011, Pages 586-594

doi:10.1016/j.engappai.2011.01.006

Abstract

In this paper, we describe the development of an extended migration operator, which combats the negative effects of noise on the effective search capabilities of genetic algorithms. The research is motivated by the need to minimise the number of evaluations during hardware-in-the-loop experimentation, which can carry a significant cost penalty in terms of time or financial expense. The authors build on previous research, where convergence for search methods such as simulated annealing and variable neighbourhood search was accelerated by the implementation of an adaptive decision support operator. This methodology was found to be effective in searching noisy data surfaces. Providing that noise is not too significant, genetic algorithms can prove even more effective guiding experimentation. It will be shown that with the introduction of a controlled migration operator into the GA heuristic, data, which represents a significant signal-to-noise ratio, can be searched with significant beneficial effects on the efficiency of hardware-in-the-loop experimentation, without a priori parameter tuning. The method is tested on an engine-in-the-loop experimental example, and shown to bring significant performance benefits.

Keywords: Genetic algorithms; Hardware-in-the-loop; Migration; Response surfaces; Engines