Spatial branch-and-bound for non-convex separable piecewise-linear optimization
Nonconvex separable piecewise-linear functions (PLFs) are widespread in Operations Research due to their frequent appearance in applications and their use to approximate nonlinearitites. Commonly, nonconvex PLFs are approached from the perspective of discrete optimisation, using special ordered sets and mixed integer linear programs (MILPs). In contrast, we take the viewpoint of global continuous optimization and … Read more