Multiobjective Decision Making (MODM) has been
suggested for the solution of complicated decision
problems. Decision analysis in numerous areas, including
industrial energy and environmental planning, necessarily
requires consideration of multiple conflicting
objectives. MODM has been successfully applied to
a number of these problems of this type. Moreover, it
has the ability to deal with both quantitative and
qualitative factors, each which involve different units
of measurement.
The objective of this study is to introduce a MODM
process for energy and environmental planning problems
in forest products manufacturing industries. Throughout
the analytic process, the posteriori articulation
of decision maker's (DM) preferences is assumed. This
mandates development of two procedures: (1) the generation
of nondominated solutions and (2) evaluation of
the solutions by DM judgement to determine the final,
best-compromised solution.
For the first procedure, a Multiobjective Linear
Programming (MOLP) model is introduced, formulated as a
prototype example through the examination of fuel-mix
options. Three objectives are observed in the MOLP
model, including: (1) total energy costs, (2) environmental
impacts, and (3) business and performance risks.
In order to overcome the complexities caused by the use
of different qualitative units of measurement, factors
(2) and (3) are quantified in numerical values. The
constraint method is then applied for the generation of
nondominated solutions. As the second procedure, an
evaluation procedure which includes multiple screening
methods is proposed for ease of problem application for
consideration of a large number of alternatives. This
methodology is based on rating and pairwise comparison
methods. Special emphasis is placed on the achievement
of a higher DM level of confidence when the final solution
is selected. The methodology can be divided into
two regions: (1) step-by-step reduction of alternatives,
and (2) judgmental options for upgrading DM confidence.
This methodology provides a useful and flexible
tool for problems as characterized above and for
large-scale problems
