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##### Using Binary Variables to Represent Logical Conditions in Optimization Models
Technical Note QA-0786 / Published April 11, 2012 / 5 pages. Collection: Darden School of Business
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Logical conditions that link different elements of a business decision are very common in managerial practice. For example, a firm can ship only to and from warehouses that are open; patients needing MRIs can only get service in clinics that have MRI equipment; regarding an old power plant, one can decide to close it or retrofit it, but one obviously cannot retrofit a closed plant. The list goes on. In quantitative modeling of such situations, a natural step is to use IF statements such as IF(a warehouse in city N is open, then we can ship to/from it; otherwise no shipments can be made in/out of a warehouse in N). In optimization models, however, IF statements lead to non-linearity with all the associated challenges. Fortunately, nearly all logical conditions can be modeled linearly using binary variables. This note describes some helpful modeling techniques for doing that.

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• Overview

Logical conditions that link different elements of a business decision are very common in managerial practice. For example, a firm can ship only to and from warehouses that are open; patients needing MRIs can only get service in clinics that have MRI equipment; regarding an old power plant, one can decide to close it or retrofit it, but one obviously cannot retrofit a closed plant. The list goes on. In quantitative modeling of such situations, a natural step is to use IF statements such as IF(a warehouse in city N is open, then we can ship to/from it; otherwise no shipments can be made in/out of a warehouse in N). In optimization models, however, IF statements lead to non-linearity with all the associated challenges. Fortunately, nearly all logical conditions can be modeled linearly using binary variables. This note describes some helpful modeling techniques for doing that.

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