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| Content Provider | Springer Nature Link |
|---|---|
| Author | Rajabalipour Cheshmehgaz, Hossein Islam, Md. Nazrul Desa, Mohammad Ishak |
| Copyright Year | 2012 |
| Abstract | In practical multi-objective optimization problems, respective decision-makers might be interested in some optimal solutions that have objective values closer to their specified values. Guided multi-objective evolutionary algorithms (guided MOEAs) have been significantly used to guide their evolutionary search direction toward these optimal solutions using by decision makers. However, most guided MOEAs need to be iteratively and interactively evaluated and then guided by decision-makers through re-formulating or re-weighting objectives, and it might negatively affect the algorithms performance. In this paper, a novel guided MOEA that uses a dynamic polar-based region around a particular point in objective space is proposed. Based on the region, new selection operations are designed such that the algorithm can guide the evolutionary search toward optimal solutions that are close to the particular point in objective space without the iterative and interactive efforts. The proposed guided MOEA is tested on the multi-criteria decision-making problem of flexible logistics network design with different desired points. Experimental results show that the proposed guided MOEA outperforms two most effective guided and non-guided MOEAs, R-NSGA-II and NSGA-II. |
| Starting Page | 699 |
| Ending Page | 726 |
| Page Count | 28 |
| File Format | |
| ISSN | 09565515 |
| Journal | Journal of Intelligent Manufacturing |
| Volume Number | 25 |
| Issue Number | 4 |
| e-ISSN | 15728145 |
| Language | English |
| Publisher | Springer US |
| Publisher Date | 2012-11-28 |
| Publisher Place | Boston |
| Access Restriction | One Nation One Subscription (ONOS) |
| Subject Keyword | Multi-objective optimization problems Guided multi-objective evolutionary algorithms Polar coordinate system Flexible logistics network design problem Production/Logistics/Supply Chain Manufacturing, Machines, Tools Control, Robotics, Mechatronics |
| Content Type | Text |
| Resource Type | Article |
| Subject | Industrial and Manufacturing Engineering Artificial Intelligence Software |
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