The double role of the weight factor in the goal programming model

In Goal Programming model, the best solution is established in such a way that the sum of the weighted deviations from the goals is minimal. The weight factor of a given objective is composed of two components destined to represent two different roles. The first one is “normalization” meaning to bring all deviations to a common unit of measurement based on the degree of proximity to the goal. The second is “valorization” reflecting the decision-maker's preference structure. The weight factor related to an objective is not a simple constant but a function of the realized level of objectives. Because of this variable nature of the weights this model will be non-linear. To cope with this problem we intend to obtain an equivalent linear presentation so that the problem can be solved using standard software suitable for mixed linear programs.