Stochastic Fractal Search Algorithm in Permutation Flowshop Scheduling Problem

In this paper, permutation flowshop scheduling problem is solved using stochastic fractal search algorithm to find a sequence of jobs minimizing makespan. SFS algorithm is inspired by the phenomenon of successful growth which uses a mathematical concept called fractal. The performance of SFS algorithm to solve permutation flowshop scheduling problem was tested using standard benchmark problems of Taillard and compared with other optimization algorithms. The results have shown that the proposed SFS algorithm performs better than other algorithms on given benchmark problems for finding the best solution found so far in minimizing makespan. Moreover, comparing with the best-known result, SFS successfully provides solutions which are near-optimal solutions.