%0 Journal Article
%T Generalized Transformation Techniques for Multi-Choice Linear Programming Problems
%A Srikumar ACHARYA
%A Mitali Madhumita ACHARYA
%J International Journal of Optimization and Control : Theories & Applications
%D 2013
%I International Journal of Optimization and Control
%X The multi-choice programming allows the decision maker to consider multiple number of resources for each constraint or goal. Multi-choice linear programming problem can not be solved directly using the traditional linear programming technique. However, to deal with the multi-choice parameters, multiplicative terms of binary variables may be used in the transformed mathematical model. Recently, Biswal and Acharya (2009) have proposed a methodology to transform the multi-choice linear programming problem to an equivalent mathematical programming model, which can accommodate a maximum of eight goals in righthand side of any constraint. In this paper we present two models as generalized transformation of the multi-choice linear programming problem. Using any one of the transformation techniques a decision maker can handle a parameter with nite number of choices. Binary variables are introduced to formulate a non-linear mixed integer programming model. Using a non-linear programming software optimal solution of the proposed model can be obtained. Finally, a numerical example is presented to illustrate the transformation technique and the solution procedure.
%K Linear programming
%K mixed integer programming
%K multi-choice programming
%K non-linear programming
%K transformation technique
%U http://dx.doi.org/10.11121/ijocta.01.2013.00132