One of the most important problems in research and applied fields of production management is a suitable scheduling for different operations. So, there are many approaches for job workshop or job non-workshop scheduling problems. Since job workshop scheduling problems (JSP) belong to NP-Hard class, some metaheuristics methods such as Tabu Search, Simulated Annealing, Genetic Algorithm and Particle Swarm Optimization have used in different papers to solve such problems. This paper tries to solve these problems by using these algorithms and compares their conclusions. Therefore, problems with different sizes are used and are analyzed by time, quantified, and parametric approaches.