Abstract
It becomes difficult to obtain an optimal combination or permutation of objects as the number of objects increases. In such cases good suboptimal solutions are valuable in practice. This paper proposes a heuristic method of obtaining suboptimal solutions of the above combinatorial optimization problems. Its basic idea is to reduce an original problem to a small one by regarding similar objects as the same. The inherent knowledge about the original problem is used for this partially identifying approximation. Suboptimal solutions of the original problem are constructed from the exact optimal solution of the reduced problem. The paper then applies the method to flow-shop scheduling problems, and discusses the effects of problem structures on the precision of obtained suboptimal solutions and the computation amount. The method seems to be easily applied to the actual large problems, because its principle is simple to understand.
