2.3. Goal programming
GP is a multi-objective decision making approach that can effectively
handle multiple independent or conflicting objectives simultaneously.
As a modification and extension of linear programming,
GP serves to minimize an objective function that can be defined as
a combination of multidimensional absolute deviations from the
target value. GP has wide usability and flexibility because of its
capability to admit nonhomogeneous units of measure (Bertolini
& Bevilacqua, 2006).
GP can be classified into two widely used variants that are distinguished
by the way they determine weights (or priorities) and
objective functions (Bertolini & Bevilacqua, 2006; Ignizio, 1980).
First, the preemptive GP model, also known as the lexicographic
GP model, is formed when goals are clearly ranked and deviation
variables are ranked. Second, the weighted GP model, also called
the nonpreemptive GP model, attempts to minimize the total
weighted deviations from all goals. This latter model is useful
when the relative weights of decision elements for goals are
available.
In the present study, we used the weighted GP model with additional
hard constraints and integer decision variables that can be
formulated as follows (Min & Storbeck, 1991):