Teaching Use of Binary Variables in Integer Linear Programs: Formulating Logical Conditions

Scott P. Stevens () and Susan W. Palocsay ()
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Scott P. Stevens: Computer Information Systems and Business Analytics Department, James Madison University, Harrisonburg, Virginia 22807
Susan W. Palocsay: Computer Information Systems and Business Analytics Department, James Madison University, Harrisonburg, Virginia 22807

INFORMS Transactions on Education, 2017, vol. 18, issue 1, 28-36

Abstract: Binary variables are often needed in linear programming models to indicate whether particular alternatives should be implemented and to impose logical relations among decisions. However, it is usually not obvious to students how to use binary variables to transform conditional statements of logic into linear relations. We propose to address this difficulty with a simple two-step approach. It provides rules for decomposing a conditional requirement into a group of elementary implications and then translating each of these into linear constraints. Pre- and post-test results from a sample of undergraduate business students are presented to support the effectiveness of this pedagogical approach.

Keywords: optimization modeling; integer programming; binary variables; logical conditions (search for similar items in EconPapers)
Date: 2017
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Citations: View citations in EconPapers (2)

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