Computational Optimization in Engineering Management teaches mathematical programming solvers with applications in supply chain analytics, finance, accounting, and marketing on a social network. It also discusses how to make a data driven decision based on clustering analysis. The students will perform challenging projects of finance/accounting and marketing on a social network. The students learn how to model real world problems as mathematical programming formulations and feed the models to mathematical programming solvers. This course introduces a variety of problems in supply chain analytics, finance, accounting, marketing, and social network analytics. The students model the problems and solve them on small scale of problem instances using Excel Solver Add-In. Then the problem scale is extended to large real world problem instances and the problems are solved by mathematical programming solvers. Programming in Python, the students feed a large scale of data to mathematical programming solvers and decode the output files from the solvers. 3 Credits