In the previous chapter, we covered how to solve integer programming problems using Solver. We also introduced the use of binary variables, which represent yes/no decisions, and we saw how binary variables arise naturally in set covering, set packing, and set partitioning. In this chapter, we expand the use of binary variables in connection with relationships we call logical constraints that restrict consideration to certain combinations of variables. Normally, we might not immediately think of these restrictions as linear constraints, but we can capture them in linear form with the use of binary variables.

We begin with the illustration of a counting constraint. This term refers to a quantitative constraint for counting our decisions, and the use of binary variables makes counting easy. As an example, we revisit the capital budgeting problem, which, in its basic form, is a pure integer program containing binary variables and one constraint. We encountered this structure in Example 6.2, in the Newton Corporation.

Get Optimization Modeling with Spreadsheets, 3rd Edition now with the O’Reilly learning platform.

O’Reilly members experience live online training, plus books, videos, and digital content from nearly 200 publishers.