Minimizing the total completion time (makespan) is an important job for a shop floor engineer so that all the jobs are completed before the due date. For smaller problems involving a few machines and jobs, finding an optimal sequence and its corresponding makespan is comparatively easier. Johnson's algorithm produces optimum makespan for the two machines, 'n' jobs permutation flow shop scheduling problems. If the number of machines is more than two, the problem is NP-Complete and the computation time grows exponentially for finding an optimal solution. Hence, various heuristic procedures have been proposed over the years for finding near optimal solutions in a reasonable time period. After the invention of computers with increased processing capabilities, various metaheuristics have been tried using iterative procedures to refine the solution obtained from the simple heuristics like the popular NEH heuristic. One attempt is made to analyze the improvement in the makespan when a combination of four different NEH family heuristics is used to solve the 'm' machines, 'n' jobs problems. They use different initial sequences and proceed further using the job insertion technique. Ruben Ruiz benchmark problems are used for the analysis, and the improvement is observed to be significant. Hence, the solution makespan can be used as the initial solution for the metaheuristics to refine the makespan quickly. In the ANOVA, the F value is observed to be small (0.01) and the P value is > 0.05 (0.999) and hence, the Null Hypothesis is accepted. © Research India Publications.