Generating alternative solutions for dynamic programming-based planning problems

An approach is developed for generating alternative near-optimal solutions for dynamic programming-based planning problems. The proposed methodology improves on an existing approach in three respects. First, computational efficiencies are achieved by recomputing the optimal policy for only a subset of the total number of stages. Second, the approach can be easily structured such that there is increased variation in alternatives within the first stages. Third, the maximum allowable difference in objective function value between alternative solutions can be explicitly stated by the user. A hypothetical shortest route problem is used to illustrate the characteristics of the proposed approach. Results are also presented for a facility capacity planning problem in the municipal solid waste management area.