Optimization in multiple-objective linear programming problems with pre-emptive priorities

A decision-maker, using mathematical programming optimization models, is often faced with a choice of many alternative solutions optimizing the objective function. The decision may be based on secondary, tertiary or higher-order objectives. Such problems are usually handled using goal programming (GP) with pre-emptive priorities. Pre-emptive prioritization is discussed in the literature in the context of GP. This paper suggests that the two are separable, and presents algorithms to accomplish this. It argues that in a truly pre-emptive situation, direct lexicographical optimization of the objectives, without introduction of goals, has a number of advantages. In addition, when applied to special structure models such as transportation or assignment, this approach enables one to maintain the structure and hence the efficiency of those algorithms.