USE OF OPTIMIZATION MODELS IN PUBLIC-SECTOR PLANNING

BRILL ED (1979) USE OF OPTIMIZATION MODELS IN PUBLIC-SECTOR PLANNING, MANAGEMENT SCIENCE, Vol. 25, No. 5, pp. 413-422.

The purpose of optimization is to obtain ‘the answer’ and is useful for simple problem. However, in a public-sector problem, there are many problems for solving or optimizing because of a multitude of local optima and elusive elements. Because of the reason, the author maintains that the optimization for public-sector problem should play the role of generating alternatives and in facilitating their evaluation and elaboration. He also said that several models and new types of formulations should be required for the better optimization.

The author points out the limitation of using optimization model which are difficulties of considering equity or distribution of income, and which are empirical inadequacies in evaluating benefits and costs. Specifically, the article demonstrates that the incomplete multi-objective models usually show that the optimal solution in public-sector problem occurs at inferior region, not at non-inferior region. Even if the model was completely formulated, it is impossible to obtain the overall best solution.

To reduce the limitations, the author suggests several methods to make the optimization models play the important role of providing alternatives for decision makers in public-sector problems. First, ‘joint use of models’ should be used such as combining analytical and optimization models or using a tool box of models. The author also recommends us to use optimization models which generate alternatives and facilitate evaluation such as branch-and-bound method, random method, and HSJ method.

In conclusion, the solution of optimization model would be a synthesized solution resulting in their alternatives, which require unlike formulations and methods. Planners and their decision can be aided by the offered alternatives with gaining better understanding of the relationship, objectives, and constraints in public-sector problems.

Discussion

Generating alternatives from a solution in a specific optimization model is interesting because people’s thinking cannot be formulated. By offering alternatives, decision makers can refer to the alternatives and they could not always select the optimal solution, but could possibly select one of the alternatives. However, I think that the article is necessary to provide more various ways or methods to generate such alternatives, and we need to improve or invent skills generating alternatives for the future research or their application.