Article ID: | iaor20163639 |
Volume: | 66 |
Issue: | 3 |
Start Page Number: | 417 |
End Page Number: | 437 |
Publication Date: | Nov 2016 |
Journal: | Journal of Global Optimization |
Authors: | Shoemaker Christine, Krityakierne Tipaluck, Akhtar Taimoor |
Keywords: | programming: multiple criteria, heuristics, heuristics: tabu search |
This paper presents a parallel surrogate‐based global optimization method for computationally expensive objective functions that is more effective for larger numbers of processors. To reach this goal, we integrated concepts from multi‐objective optimization and tabu search into, single objective, surrogate optimization. Our proposed derivative‐free algorithm, called SOP, uses non‐dominated sorting of points for which the expensive function has been previously evaluated. The two objectives are the expensive function value of the point and the minimum distance of the point to previously evaluated points. Based on the results of non‐dominated sorting,