Abstract

In this paper, we develop efficient heuristic algorithms for multiprocessor task scheduling in a two-stage flow-shop environment to minimize makespan. We also derive a very effective lower bound for the problem. Then, we analyze the worst case error-bound of the heuristic algorithms. Next, we perform computational experiments to analyze the performance of the heuristic algorithms by computing the average percentage deviation of each heuristic solution from the lower bound. The results of the computational experiment on a set of randomly generated problems show that the proposed heuristic algorithms perform well. Furthermore, we consider the reverse problem and show that the two problems are equivalent. Finally, we identify a special case of the problem that is polynomially solvable.

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