Mixed-Integer Models for Nonseparable Piecewise-Linear Optimization: Unifying Framework and Extensions
نویسندگان
چکیده
منابع مشابه
Mixed-Integer Models for Nonseparable Piecewise-Linear Optimization: Unifying Framework and Extensions
We study the modeling of non-convex piecewise linear functions as Mixed Integer Programming (MIP) problems. We review several new and existing MIP formulations for continuous piecewise linear functions with special attention paid to multivariate non-separable functions. We compare these formulations with respect to their theoretical properties and their relative computational performance. In ad...
متن کاملParallel Solvers for Mixed Integer Linear Optimization
In this article, we provide an overview of the current state of the art with respect to solution of mixed integer linear optimization problems (MILPS) in parallel. Sequential algorithms for solving MILPs have improved substantially in the last two decades and commercial MILP solvers are now considered effective off-the-shelf tools for optimization. Although concerted development of parallel MIL...
متن کاملA Comparison of Mixed - Integer Programming Models for Nonconvex Piecewise Linear Cost Minimization Problems
We study a generic minimization problem with separable non-convex piecewise linear costs, showing that the linear programming (LP) relaxation of three textbook mixed-integer programming formulations each approximates the cost function by its lower convex envelope. We also show a relationship between this result and classical Lagrangian duality theory.
متن کاملTrajectory Optimization using Mixed-Integer Linear Programming
This thesis presents methods for finding optimal trajectories for vehicles subjected to avoidance and assignment requirements. The former include avoidance of collisions with obstacles or other vehicles and avoidance of thruster plumes from spacecraft. Assignment refers to the inclusion of decisions about terminal constraints in the optimization, such as assignment of waypoints to UAVs and the ...
متن کاملMISO: Mixed-Integer Surrogate Optimization Framework
We introduce MISO, the Mixed-Integer Surrogate Optimization framework. MISO aims at solving computationally expensive black-box optimization problems with mixed-integer variables. Although encountered in many applications, such as optimal reliability design or structural optimization, for example, where time consuming simulation codes have to be run in order to obtain an objective function valu...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Operations Research
سال: 2010
ISSN: 0030-364X,1526-5463
DOI: 10.1287/opre.1090.0721