I-MODE: an interactive multi-objective optimization and decision-making using evolutionary methods

Deb, Kalyanmoy ; Chaudhuri, Shamik (2007) I-MODE: an interactive multi-objective optimization and decision-making using evolutionary methods Lecture Notes in Computer Science, 4403 . pp. 788-802. ISSN 0302-9743

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Official URL: http://www.springerlink.com/content/7k6853627k6066...

Related URL: http://dx.doi.org/10.1007/978-3-540-70928-2_59


With the popularity of efficient multi-objective evolutionary optimization (EMO) techniques and the need for such problem-solving activities in practice, EMO methodologies and EMO research and application have received a great deal of attention in the recent past. The first decade of research in EMO area has been spent on developing efficient algorithms for finding a well-converged and well-distributed set of Pareto-optimal solutions, although EMO researchers were always aware of the importance of procedures which would help choose one particular solution from the Pareto-optimal set for implementation. In this paper, we address this long-standing issue and suggest an interactive EMO procedure by collating most salient research in EMO and putting together a step-by-step EMO and decision-making procedure. The idea is implemented in a GUI-based, user-friendly software which allows a user to supply the problem mathematically or by using user-defined macros and enables the user to evaluate solutions directly or by calling an executable software, such as popularly-used MATLAB software for a local search or ANSYS software for finite element analysis, etc. Starting with standard EMO applications, continuing to finding robust, partial, and user-defined preferred frontiers through standard MCDM procedures, the well-coordinated software allows the user to first have an idea of the complete trade-off frontier, then systematically focus in preferred regions, and finally choose a single solution for implementation.

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