A Modified Game Theory Approach to Multiobjective Optimization

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Abstract
In todays competitive economy, it is no longer possible for the designer to find solutions to conflicting objective problems which are merely adequate. The designer must select the design variables such that there is a superior compromise between the objectives. To this end, a large number of methods have been developed for the solution of multiobjective optimization problems. The earliest reported in-depth work on the formulation of the multiobjective problem is that of Kuhn and Tucker [1]. Reviews of the progress in the field have been published by Hwang and Masud [2], Stadler [3], Evans [4], and Rastrigin and Eiduk [5]. The methods for optimizing multiple objectives may be categorized into two types, leaving the objectives in vector form and scalarizing the objectives into one equation.

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