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11 - Computer Science and Informatics

Heriot-Watt University

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Output 48 of 91 in the submission

Output title

MOPC/D: A new Probability Collectives algorithm for Multiobjective Optimisation

Type

E - Conference contribution

DOI

10.1109/MCDM.2013.6595439

Name of conference/published proceedings

IEEE Symposium Series on Computational Intelligence

Volume number

Issue number

First page of article

tba

ISSN of proceedings

Year of publication

2013

URL

Number of additional authors

Additional information

<22>This paper is the main output to date from Corne's SEAS DTC grant with Waldock (BAE Systems), which was the first to invent algorithms for multi-objective optimization (MOO) in the novel 'probability collectives' (PC) optimization framework (http://collectives.stanford.edu/Library/). Our derivation and development of MOO in the PC context led to EP Patent 2,497,03 and US Patent 20,120,226,654 (Waldock and Corne are the patent authors in both cases). This paper demonstrates performance that advances the state of the art in multiobjective optimization. Waldock is Technology Lead for Information Processing at BAE Systems Advanced Technology Centre, antony.waldock@baesystems.com.

Interdisciplinary

Cross-referral requested

Research group

A - Intelligent Systems

Citation count

Proposed double-weighted

Double-weighted statement

Reserve for a double-weighted output

Non-English

English abstract