Skip to main content

Research Repository

Advanced Search

Improved dynamic lexicographic ordering for multi-objective optimisation

Castro-Gutierrez, Juan; Landa-Silva, Dario; Moreno-Perez, Jose A.

Authors

Juan Castro-Gutierrez

Jose A. Moreno-Perez



Abstract

There is a variety of methods for ranking objectives in multiobjective optimization and some are difficult to define because they require information a priori (e.g. establishing weights in a weighted approach or setting the ordering in a lexicographic approach). In manyobjective optimization problems, those methods may exhibit poor diversification and intensification performance. We propose the Dynamic Lexicographic Approach (DLA). In this ranking method, the priorities are not fixed, but they change throughout the search process. As a result, the search process is less liable to get stuck in local optima and therefore, DLA offers a wider exploration in the objective space. In this work, DLA is compared to Pareto dominance and lexicographic ordering as ranking methods within a Discrete Particle Swarm Optimization algorithm tackling the Vehicle Routing Problem with Time Windows.

Citation

Castro-Gutierrez, J., Landa-Silva, D., & Moreno-Perez, J. A. (2010). Improved dynamic lexicographic ordering for multi-objective optimisation

Conference Name Parallel Problem Solving from Nature - PPSN XI, Lecture Notes in Computer Science, Vol. 6239
End Date Sep 15, 2010
Acceptance Date Jul 11, 2010
Publication Date Sep 11, 2010
Deposit Date Aug 1, 2016
Publicly Available Date Aug 1, 2016
Peer Reviewed Peer Reviewed
Keywords multiobjective optimization, vehicle routing, swarm optimization
Public URL http://eprints.nottingham.ac.uk/id/eprint/35589
Publisher URL http://link.springer.com/chapter/10.1007%2F978-3-642-15871-1_4
Copyright Statement Copyright information regarding this work can be found at the following address: http://eprints.nottingham.ac.uk/end_user_agreement.pdf
Additional Information Note: Presented at the 11th International Conference on Parallel Problem Solving From Nature (PPSN 2010), Krakow Poland, September 2010. doi: 10.1007/978-3-642-15871-1_4

Files


dls_ppsn2010.pdf (180 Kb)
PDF

Copyright Statement
Copyright information regarding this work can be found at the following address: http://eprints.nottingham.ac.uk/end_user_agreement.pdf





You might also like



Downloadable Citations