When solving integer programming problems, how does the branch and bound method handle nonlinear constraints?
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Hybrid approaches combine elements of different optimization techniques to address the challenges posed by nonlinear constraints. For example, a solver might use a combination of B&B, convex optimization, and heuristics to navigate the solution space.
In Operations Research Integer Linear Programming, the branch and bound method systematically explores the solution space of integer programming problems by iteratively partitioning the feasible region and using linear relaxations to handle nonlinear constraints.
Nonlinear constraints can sometimes be approximated using piecewise linear functions. The B&B algorithm can then work with these piecewise linear approximations to generate bounds and explore the solution space.