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Are the "Best" Solutions to a Real Optimization Problem Always Found in the Noninferior Set? Evolutionary Algorithm for Generating Alternatives (EAGA)
Emily M. Zechman and S. Ranji Ranjithan
North Carolina State University
CB 7908
Raleigh, NC 27695, USA
{emzechma,ranji}@eos.ncsu.edu
Abstract. Evolutionary algorithms (EAs) continue to offer an effective, powerful, and sometimes exclusive way to search for solutions to real optimization problems. While these algorithms can help solve a complex optimization problem, whether the results represent the "best" choices for making decisions about a solution to a real problem is questionable. In decision-making problems that are ill posed, all objectives may not be defined clearly and therefore not quantitatively captured in the optimization model [1]. The noninferior set of solutions to the optimization model being solved may not necessarily contain the best solution to the actual problem.
LNCS 2724, p. 1622 ff.
lncs@springer.de
© Springer-Verlag Berlin Heidelberg 2003