Abstract

another, so that it is not possible to improve on any of the objective functions without deteriorating at least one of the other objective functions. This is known as the concept of Pareto optimality (Rao, 1991). In multiobjective optimization, as opposed to single-objective optimization, there may not exist an unambigous optimal solution (global minimum or global maximum). Characteristic of the multiobjective optimization problems is a very large set of acceptable solutions that are superior to the rest of the solutions in the search space when all objectives are considered. At the same time they are not optimal from the point of any single objective. These solutions are known as Pareto-optimal solutions or nondominated solutions. The rest of the solutions are referred to as dominated solutions. Since none of the solutions in a Pareto-optimal set is absolutely better than any other, any one of them is an acceptable solution. The choice of one particular solution depends on the feature...

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