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Engineering design often requires that one consider§multiple criteria; pursuing just one objective can be§insufficient. The process of optimizing a collection§of objective functions is called multi-objective§optimization, and it necessitates the use special§optimization methods. Potential applications for even§the most fundamental and common methods span a§variety fields. Consequently, the significance of any§contribution to this process is far reaching, with§implications in terms of computational problem§solving and in terms of conceptual decision-making.§However, the study of fundamental methods has been§deficient. Critical information concerning the§significance of method-parameters, the effect of§formulation variations, and guidelines for effective§use has been unrevealed, and drawbacks of different§methods have not been explored. This work responds§to these deficiencies on three levels: 1) qualitative§assessment, 2) analysis with consequent enhancements§and guidelines, and 3) application to significant§problems. New in-depth analysis reveals useful§insight into how the methods work, fosters new§methods, and provides method augmentation that§improves performance.
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