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Mixed integer optimization (MIP) determines optimal solutions of such complex problems; the development of new algorithms, software and hardware allow the solution of larger problems in acceptable times.
Cutting Planes give a way to reduce the search space for the optimal solution in an integer optimization problem.
Initially, an integer optimization problem is formulated to identify optimal distributions of inputs and outputs (decentralized control configurations) that minimize the overall structural coupling in the network.
This problem belongs to the class of nonlinear integer optimization programs, which have no general global optimal solution.
Optimal solutions by mixed-integer programming For certain classes of mixed integer optimization problems, fast solver implementations are available that guarantee to find the optimal solution.
"Learning a Mixture of Gaussians via Mixed Integer Optimization". Bandi, Hari, Dimitris Bertsimas, and Rahul Mazumder.
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The problem is formulated as a mixed-integer optimization.
Our method leverages a natural decomposition of the routing problem, computing and combining subproblem solutions via mixed-integer optimization.
A tailored two-step solution strategy is proposed to tackle the robust mixed-integer optimization problem.
The problem is formulated as a mixed-integer optimization problem that accounts for time and congestion dependent vehicle speeds.
Second, we discuss logic-based optimization and its influence in both modeling and solving mixed-integer optimization problems.
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