@InProceedings{10.1007/978-3-540-70928-2_59,
author="Deb, Kalyanmoy
and Chaudhuri, Shamik",
editor="Obayashi, Shigeru
and Deb, Kalyanmoy
and Poloni, Carlo
and Hiroyasu, Tomoyuki
and Murata, Tadahiko",
title="I-MODE: An Interactive Multi-objective Optimization and Decision-Making Using Evolutionary Methods",
booktitle="Evolutionary Multi-Criterion Optimization",
year="2007",
publisher="Springer Berlin Heidelberg",
address="Berlin, Heidelberg",
pages="788--802",
abstract="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.",
isbn="978-3-540-70928-2"
}