For some optimization problems, the variables should not take on fractional values. For instance, if a variable represents the number of stock shares to purchase, it should take on only integer values. Similarly, if a variable represents the on/off state of a generator, it should take on only binary values (0 or 1). The mixed-integer linear programming problem allows this behavior to be modeled by adding the constraint that these variables should take on only integers, or whole numbers, in the optimal solution.
Mixed-Integer Linear Programming in MATLAB
Learn how to use the new optimization solver for mixed-integer linear programming in Release 2014a. This new solver enables you to solve optimization problems in which some or all of the variables are constrained to take on integer values.
Optimization Toolbox solves mixed-integer linear programming problems using an algorithm that:
You can use Optimization Toolbox solvers with MATLAB Compiler™ to create decision support tools that can be shared with users who do not have MATLAB. These standalone applications can be deployed royalty-free to an unlimited number of end users. You can also integrate MATLAB optimization algorithms with other languages, such as Java® and .NET, using MATLAB Builder™ products.