A Hybrid Genetic Simulated Annealing Algorithm in the Retardance Optimization of Citrate Coated Ferrofluid

In this paper, a hybrid of genetic algorithm (GA) and simulated annealing (SA) algorithm (HGSA) is developed to optimize the retardance in citrate (citric acid, CA) coated ferrofluids (FFs). The HGSA not only can overcome the deficiency of GA but also increase the possibility of finding the global solution by using SA. It enhances the ability of local searching by using SA. Initially, two factors that affect the performance of SA as initial temperature and cooling rate are decided. The maximum retardance is found as 42.4058° with a parametric combination of [5.5, 0.12, 40, 90], corresponding to pH of suspension, molar ratio of CA to Fe3O4, CA volume, and coating temperature. Moreover, when executing the HGSA algorithm, two parametric combinations of [5.499, 0.12, 39.369, 90] and [5.496, 0.106, 39.832, 89.976] associated with maximum and minimum retardance obtained by GA are adopted as the start points in the simulation of SA algorithm. Hence, a better solution of 42.4313° with [5.5, 0.12, 38.733, 90] is sought successfully. The hybrid of GA and SA can improve the solving efficiency.