A Sequential Multi-Objective Robust Optimization Approach under Interval Uncertainty Based on Support Vector Machines
| Title | A Sequential Multi-Objective Robust Optimization Approach under Interval Uncertainty Based on Support Vector Machines |
| Publication Type | Conference Paper |
| Year of Publication | 2017 |
| Authors | Xie, T., Zhou, Q., Hu, J., Shu, L., Jiang, P. |
| Conference Name | 2017 IEEE International Conference on Industrial Engineering and Engineering Management (IEEM) |
| Date Published | dec |
| Keywords | composability, Computational modeling, convergence, design alternative classification model, genetic algorithms, interval uncertainty, mathematics computing, Metrics, multi-objective robust optimization, optimisation, Optimization, pattern classification, pubcrawl, resilience, Resiliency, Robustness, sequential MORO, sequential multiobjective robust optimization, sequential optimization approach, Support vector machines, SVM, Uncertainty |
| Abstract | Interval uncertainty can cause uncontrollable variations in the objective and constraint values, which could seriously deteriorate the performance or even change the feasibility of the optimal solutions. Robust optimization is to obtain solutions that are optimal and minimally sensitive to uncertainty. In this paper, a sequential multi-objective robust optimization (MORO) approach based on support vector machines (SVM) is proposed. Firstly, a sequential optimization structure is adopted to ease the computational burden. Secondly, SVM is used to construct a classification model to classify design alternatives into feasible or infeasible. The proposed approach is tested on a numerical example and an engineering case. Results illustrate that the proposed approach can reasonably approximate solutions obtained from the existing sequential MORO approach (SMORO), while the computational costs are significantly reduced compared with those of SMORO. |
| URL | https://ieeexplore.ieee.org/document/8290260/ |
| DOI | 10.1109/IEEM.2017.8290260 |
| Citation Key | xie_sequential_2017 |
- pattern classification
- uncertainty
- SVM
- Support vector machines
- sequential optimization approach
- sequential multiobjective robust optimization
- sequential MORO
- Robustness
- Resiliency
- resilience
- pubcrawl
- composability
- optimization
- optimisation
- multi-objective robust optimization
- Metrics
- mathematics computing
- interval uncertainty
- genetic algorithms
- design alternative classification model
- convergence
- Computational modeling