A Survey of Mixed Integer Nonlinear Optimization
Sven Leyffer, Argonne National Laboratory
Many optimization problems involve variables which are restricted
to take binary, integral or discrete values. Applications include
chemical engineering such as process synthesis, batch plant design,
cyclic scheduling or the design of distillation columns. More recently,
applications have arisen in the nuclear industry, to optimize core
reload operations and in topology optimization, where binary variables
model the presence or absence of material in each finite element.
This talk surveys the recent developments in the design of solvers
for large Mixed Integer Nonlinear Programming (MINLP) problems. It
will start by reviewing classical methods such as branch-and-bound,
Benders Decomposition and Outer Approximation. Next, new hybrid
approaches, combining these classical methods are discussed and
likely future challenge and developments are pointed out.
Chemnitz Workshop
Last modified: Mon Sep 23 18:53:51 CEST 2004