Abolfazl Adressi - Department of Industrial Engineering, K.N.Toosi University of Technology, Iran
Reza Bashirzadeh - Department of Industrial Engineering, K.N.Toosi University of Technology, Iran
Vahid Azizi - Department of Industrial Engineering, K.N.Toosi University of Technology, Iran
Saeed Tasouji Hassanpour - Faculty of Industrial Engineering, Tarbiat Modares University (TMU), Iran, Tehran

Different manufacturing enterprises use regularly scheduling algorithms in order to help meeting demands over time and reducing operational costs. Nowadays, for a better useofresources and manufacturingin accordance withcustomer needs and given the level ofcompetitionbetweencompanies, employing asuitablescheduling programhasa double importance. Conventional productionmethods are constantly substituted with new ones for improving the efficiency and effectiveness of the entire production system. In this paper, two Meta-heuristic algorithms, Genetic and simulated annealing, have been used in order to solve the group scheduling problem of jobs in a single stage No-wait flow shop environment in which setup times are sequence dependent,. The purpose of solving the proposed problem is to minimize the maximum time needed to complete the jobs (Makespan). The results show that Genetic algorithm is efficient in problems with small and large dimensions, with respect to time parameter of problem solving.

Group Scheduling, No-wait Flow Shop, Sequence Dependent Setup Times, Metaheuristic Algorithms