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This paper proposes a mechanism that is capable of learning the appropriate simulation run length for each solution and provides much better solution ...
Abstract—For many real-world optimization problems, eval- uating a solution involves running a computationally expensive simulation model.
As we demonstrate, our proposed algorithm finds good solutions much faster than always using the full computational fluid dynamics simulation and provides much ...
Efficient use of partially converged simulations in evolutionary optimization. J Branke, M Asafuddoula, KS Bhattacharjee, T Ray. IEEE Transactions on ...
In this paper, we propose an algorithm M3EA to solve computationally expensive multi/many-objective optimization problems with multiple fidelity levels.
(2017) Efficient Use of Partially Converged Simulations in Evolutionary Optimization, IEEE Transactions on Evolutionary Computation 21(1):52--64. Digital ...
This paper focuses on theoretical analysis of a (1+1) surrogate-assisted evolutionary algorithm ((1+1)SAEA), which consists of one individual and pre-evaluates ...
The main objective of this paper is to propose an optimization strategy which uses partially converged data to minimize the computational effort associated ...
... Efficient Use of Partially Converged Simulations in Evolutionary Optimization," IEEE Transactions on Evolutionary Computation, vol. 21m issue 1, pp. 52-64 ...
2006/03/06 · We now present a strategy for utilizing a surrogate model built from partially converged simulations, such as the optimum DoE derived from ...