Abstract

Linear programming (LP) is an optimization model in which the objective functions and the constraints are strictly linear. It is used in a wide range of areas such as agriculture, transportation, economics, and industry. Advent of computers has made it the backbone of solution algorithms for other OR models including integer, stochastic, and nonlinear programming. In this chapter, we discuss a two-variable LP model and present its graphical solution. The LP model will contain an objective function, set of constraints, and non-negativity restrictions. Each component will be evaluated on one or more of the following: decision variables, objective function coefficients, technical coefficients, and resources availability. The key takeaways for the reader from this chapter are listed below: A good understanding of LP problems. Formulation of the two-variable LP problem. Understanding optimization in the contexts of minimization and maximization objective functions. Representing a two-variable LP model graphically.

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 call

Disclaimer: 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.