Name
Abstract | ||
|---|---|---|
Evolutionary multicriteria optimization has traditionally concentrated on problems comprising 2 or 3 objectives. While engineering design problems can often be conveniently formulated as multiobjective optimization problems, these often comprise a relatively large number of objectives. Such problems pose new challenges for algorithm design, visualisation and implementation. Each of these three topics is addressed. Progressive articulation of design preferences is demonstrated to assist in reducing the region of interest for the search and, thereby, simplified the problem. Parallel coordinates have proved a useful tool for visualising many objectives in a two-dimensional graph and the computational grid and wireless Personal Digital Assistants offer technological solutions to implementation difficulties arising in complex system design. |
Year | DOI | Venue |
|---|---|---|
2005 | 10.1007/978-3-540-31880-4_2 | EMO |
Keywords | Field | DocType |
complex system design,engineering design problem,evolutionary multicriteria optimization,implementation difficulty,large number,many-objective optimization,multiobjective optimization problem,algorithm design,new challenge,computational grid,engineering design perspective,design preference,engineering design,multiobjective optimization,complex system,parallel coordinates,multicriteria optimization,region of interest | Probabilistic-based design optimization,Algorithm design,Industrial engineering,Visualization,Computer science,Multi-objective optimization,Parallel coordinates,Engineering design process,Engineering optimization,Grid,Management science | Conference |
Volume | ISSN | ISBN |
3410 | 0302-9743 | 3-540-24983-4 |
Citations | PageRank | References |
124 | 4.06 | 10 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Peter J. Fleming | 1 | 3023 | 475.23 |
| Robin C. Purshouse | 2 | 628 | 30.00 |
| Robert J. Lygoe | 3 | 163 | 6.42 |