Performance measurement of selected heuristic algorithms for solving scheduling problems

The problem of scheduling in a Flow Shop is considered with the objective of minimizing the makespan for static problems. This paper compares the most common heuristics methods, namely CDS, Palmer's Slope index, Gupta's algorithm and so called MOD algorithm, for scheduling on the variety size of problem data sets and their impact on CPU time. The computational experiment includes 12 of available benchmark data sets of 10 problems proposed by Taillard. The results are computed and presented in the form of relative percentage deviation with the boundaries to the reference heuristic, namely NEH algorithm. Computational experiments are conducted to evaluate the impact of scheduling problem datasets of n-job and m-machine in flow-shop on CPU time.