Abstract
In this chapter, we study mixed-integer linear optimization problems, which are also known as mixed-integer linear programming problems (MILPPs). MILPPs are problems with an objective function and constraints that all linear in the decision variables. What sets MILPPs apart from linear optimization problems is that at least some of the variables in MILPPs are constrained to take on integer values. This chapter provides examples to show the practical significance of MILPPs. We also demonstrate the use of a special type of integer variable known as a binary variable, to model a number of types of nonlinearities and discontinuities while maintaining a linear model structure. Two solution techniques for MILPPs are also introduced.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
