The paper deals with testing and evaluation of selected heuristic optimization methods - Random Search, Downhill Simplex, Hill
Climbing, Tabu Search, Local Search, Simulated Annealing, Evolution Strategy and Differential Evolution. We modified basic
methods in such a way that they are applicable for discrete event simulation optimization purposes. The paper is mainly focused
on testing Downhill Simplex and Differential Evolution because these methods achieved below-average performances in the
initial testing of finding the global optimum. We modified these methods and we compared the modified and previous basic
versions of these methods. We proposed different evaluation criteria (criteria express the success in different ways). These
criteria use box plot characteristics calculated from the repeated optimization experiments. We have also tested different settings
of these optimization methods to analyse their behaviour considering the setup of the optimization method parameters.
The paper deals with testing and evaluation of selected heuristic optimization methods - Random Search, Downhill Simplex, HillClimbing, Tabu Search, Local Search, Simulated Annealing, Evolution Strategy and Differential Evolution. We modified basicmethods in such a way that they are applicable for discrete event simulation optimization purposes. The paper is mainly focusedon testing Downhill Simplex and Differential Evolution because these methods achieved below-average performances in theinitial testing of finding the global optimum. We modified these methods and we compared the modified and previous basicversions of these methods. We proposed different evaluation criteria (criteria express the success in different ways). Thesecriteria use box plot characteristics calculated from the repeated optimization experiments. We have also tested different settingsof these optimization methods to analyse their behaviour considering the setup of the optimization method parameters.
การแปล กรุณารอสักครู่..
