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In this paper, we describe new hybrid genetic algorithm and particle swarm optimization to solve the sum of earliness and the number of tardy job on two-machines flow shop schedule problem is NP- hard. The study discusses a hybrid genetic algorithm and particle swarm optimization (HGA-PSO) to tackle the presented mission. Extensive experiments, based on computers, suggest that the proposed mathematical models are efficient in solving flow shop problems with GA solved to n = 3000 while PSO solved to n = 500 job. [ABSTRACT FROM AUTHOR]

The benefit of this paper is to find the circular divison of the factor group when r is an odd number, where Q2r is denoted to Quaternion group of order 4r, such that for each positive integer r, there are two generators a and b for Q2r satisfies Q2r = {ah bk, 0 ≤ h ≤ 2r − 1, k = 0, 1} which has the following properties {a2r = b4 = I, barb−1 = a−r}. [ABSTRACT FROM AUTHOR]