Beyond LP and MILP Problems ⊖

Josef Kallrath
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Josef Kallrath: University of Florida

Chapter Chapter 11 in Business Optimization Using Mathematical Programming, 2021, pp 391-422 from Springer

Abstract: Abstract This chapter mentions several optimization problems which go beyond linear and mixed integer linear optimization. The focus is rather on motivation. Therefore, it is not intended to cover these topics in complete depth, but the reader should at least be aware that modeling real-world problems is not restricted to linear models. In fractional programming we show how to transform the problem to linear programming, and successive linear programming as a special solution technique of nonlinear optimization. Next, we briefly discuss stochastic optimization. For quadratic programming, which is again a special case of nonlinear optimization, we provide an equivalent formulation based on special ordered sets. Nonlinear optimization is covered in more detail in the next chapter followed by separate chapters on deterministic global optimization in practice and polylithic modeling and solution approaches.

Date: 2021
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DOI: 10.1007/978-3-030-73237-0_11

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