  Optimization has found numerous applications in engineering, particularly
since 1960s. Many optimization applications in engineering have more than one
objective (or performance criterion). Such applications require multi-objective
(or multi-criteria) optimization (MOO or MCO). Spurred by this and development
of techniques for handling multiple objectives, MOO has found many applications
in engineering in the last two decades. Optimization of an application for more
than one objective gives a set of optimal solutions (known as non-dominated or
Pareto-optimal solutions), which are equally good in the sense that no
objective can be further improved without resulting in deterioration of at
least one other objective. MOO in engineering has mainly focused on development
of a model for the application, formulation of the MOO problem and solution of
the formulated problem to find Pareto-optimal solutions. However, for
completion of MOO, one more step is required to choose one of these optimal
solutions for implementation.
