Solving linear programming problems in a spreadsheet yields equations for maximizing business profits. As applied to business, linear programming typically involves an objective formula, such as unit ...

Abstract: In a recent paper, Gongyun Zhao introduced what appears to be the first interior point formulation for solving two-stage stochastic linear programs for finite support random variables. In ...

Computing high-quality control policies in sequential decision making problems is an important task across several application domains. Markov decision processes (MDPs) provide a powerful framework to ...

Abstract: Mixed Integer Linear Programs (MILPs) are powerful tools for modeling and solving combinatorial optimization problems. Solving an MILP is NP-hard due to the integrality requirement, and the ...

Start working toward program admission and requirements right away. Work you complete in the non-credit experience will transfer to the for-credit experience when you ...

Efficiently tackling complex optimization problems, ranging from global package routing to power grid management, has been a persistent challenge. Traditional methods, notably mixed-integer linear ...