So far through our reading and homework, we have learned how linear programming can be used to solve organizational problems such as reducing costs and increasing effectiveness (of resources). However, linear programming works on the “assumption that the solutions could be fractional or real numbers (i.e., non-integer)” and this is not always practical which is why integer programming models are necessary (Taylor, 2016, p. 186). Integer programming models have three basic types (1) a total integer model, (2) a 0-1 integer model (3) and a mixed integer model (Taylor, 2016, p.186).

Our reading gives us a prime example of how these models can be used for everyday solutions. The Virginia Court of Appeals was able to use integer programming models to create an annual court schedule. Before this, court scheduling was a manual task that took 150 hours of direct labor (Taylor, 2016, p. 195). IBM sells programs to help business professional use integer programming to improve company performance. They explain how the manufacturing industry can use integer programming to solve problems dealing with blending, economic planning, farm planning, food manufacturing, and refinery planning. They also argue that other industries like supply chain can use it for product deployment, timetabling for manpower planning, and the transportation industry for network flows (IBM, 2017).