| Title |
Parallelization of multi-objective optimization methods / |
| Translation of Title |
Daugiakriterio optimizavimo metodų lygiagretinimas. |
| Authors |
Nemura, Mantas |
| Full Text |
|
| Pages |
35 |
| Keywords [eng] |
multi-objective optimization, Pareto ranking, non-dominated sorting, genetic algorithm, parallel computing, parallel optimization |
| Abstract [eng] |
The purpose of this research is to create a novel parallel optimization algorithm while focusing mainly on efficient Pareto ranking strategy. A theoretical background of multi-objective optimization and parallel computing is provided at the first part of the report. Two different Pareto ranking approaches - dominance-rank and dominance-depth - are used for algorithm implementation and hence two separate instances are distinguished. Implementation details of proposed algorithm are comprehensively explained and the performance results of two parallel ranking variants are presented and discussed. The implemented algorithm is applied to solve a facility location problem where two existing companies compete for the market. |
| Dissertation Institution |
Vilniaus universitetas. |
| Type |
Master thesis |
| Language |
English |
| Publication date |
2021 |
