Multiprocessor scheduling: combining LPT and MULTIFIT

AbstractWe consider the problem of scheduling a set of n independent jobs on m identical machines with the objective of minimizing the total finishing time. We combine the two most popular algorithms, LTP and MULTIFIT, to form a new one. MULTIFIT is well known to have better error bound than LPT with the price paid in running time. Although MULTIFIT provides a better error bound, in many cases LPT still can yield better results. This motivates the development of this new combined algorithm, which uses the result of LPT as the incumbent and then applies MULTIFIT with fewer iterations. The performance of this combined algorithm is better than that of LPT because it uses LPT as an incumbent. The error bound of this combined algorithm is never worse than that of MULTIFIT. For example, the error bound of implementing this combined algorithm to the two-processor problem is 19, compared to the error bound of 17 in MULTIFIT. Empirical results of the comparison for schedules obtained by the combined algorithm, MULTIFIT and LPT are also provided