4. Network Optimization#
In the previous chapters, we dealt with general problems by first formulating all necessary constraints and then passing the problem to an LO or MILO solver, but in a way we have been oblivious to the problem’s structure. However, it is often advantageous to analyze this structure, as it can enable us to find better solution methods. In this chapter, we consider a very general class of problems with such a special structure – the network flow problems.
This chapter includes several examples with companion Pyomo implementation that explore various modeling and implementation aspects of network optimization:
A transportation problem, using the minimum-cost flow formulation.
A scheduling problem formulated and solved as a graph coloring problem.
Go to the next chapter about convex optimization.