ABSTRACT
Decision-makers in the mineral industry, and elsewhere, frequently employ Operations Research to obtain quantitative solutions aiding their considerations. However, the complexity of the decision-making process requires flexibility which is not well-served by a single optimal solution. The paper presents a universal approach to providing the decision-maker, not only with the optimal solution, but also with a user-controlled number of marginally inferior suboptimal solutions. The approach is illustrated with two simple numerical examples: one with the objective of minimization, and the other with maximization as the optimization objective.
