Global ETD Search
Search theses and dissertations gathered from participating repositories worldwide. Every result links back to the library that holds it. No account is needed.
Results
Showing 1 to 20 of 546 for “"Mixed Integer"”.
-
On Efficient Solution Methods for Mixed-Integer Nonlinear and Mixed-Integer Quadratic Optimization Problems
… thesis we focus on solution methods for convex mixed-integer nonlinear optimization problems (MINLP). As one main result, we propose a new algorithm guaranteeing global optimality for convex MINLPs under standard assumptions. The new algorithm called MIQP-supported outer approximation (MIQPSOA) …
-
Application-oriented Mixed Integer Non-Linear Programming
… recent years there is a renovate interest for Mixed Integer Non-Linear Programming (MINLP) problems. This can be explained for different reasons: (i) the performance of solvers handling non-linear constraints was largely improved; (ii) the awareness that most of the applications from the …
-
Multi-target tracking via mixed integer optimization
… to these approaches, we propose the use of mixed integer optimization (MIO) models and local search algorithms that are (a) scalable, as they provide near optimal solutions for six targets and ten time periods in milliseconds to seconds, (b) general, as they make no assumptions on the data, …
-
Trajectory optimization using mixed-integer linear programming
… However, they can be formulated as mixed-integer linear programs (MILP) that can be solved for global optimality using powerful, commercial software. This thesis provides several extensions to previous work using MILP. The constraints for avoidance are extended to prevent plume …
-
On cutting planes for mixed-integer nonlinear programming
Mixed-integer nonlinear programming is a powerful technology that allows us to model and solve problems involving nonlinear functions, continuous, and discrete variables. The state-of-the-art solvers of mixed-integer nonlinear programs (MINLPs) use a combination of, among other techniques, branch- …
-
Enhanced Mixed Integer Programming Techniques and Routing Problems
Mixed integer programming is up today one of the most widely used techniques for dealing with hard optimization problems. On the one side, many practical optimization problems arising from real-world applications (such as, e.g., scheduling, project planning, transportation, telecommunications, …
-
Mixed Integer Nonlinear Programs: Theory, Algorithms and Applications
… for finding global optima of continuous, integer, and mixed integer nonlinear programs. The main contributions of this thesis are: (1) We develop the first constructive technique for characterizing convex envelopes of nonlinear functions. Demonstrating the technique, we derive a …
-
Application of mixed-integer programming in chemical engineering
Mixed-Integer Programming has been a vital tool for the chemical engineer in the recent decades and is employed extensively in process design and control. This dissertation presents some new Mixed-Integer Programming formulations developed for two well-studied problems, one with a central role in …
-
Stochastically Constrained Simulation Optimization On Mixed-Integer Spaces
… simulation optimization (SO) algorithm on integer spaces. cgR-SPLINE sequentially solves random restarts of a gradient-based local search routine with increasing precision. The local search routine in turn solves progressively stricter outer approximations of the underlying problem. The …
-
A Composite Algorithm for Mixed Integer Constrained Nonlinear Optimization
A composite optimization algorithm applicable to mixed integer, constrained, nonlinear problems is developed in this research. One major component of the composite algorithm is a modified version of the nonlinear simplex method. Significant modifications are made to this algorithm including the …
-
Evaluating robustness of neural networks with mixed integer programming
… of piecewise-linear neural networks as a mixed integer program. Our verifier finds minimum adversarial distortions two to three orders of magnitude more quickly than the state-of-the-art. We achieve this via tight formulations for non-linearities, as well as a novel presolve algorithm that …
-
Learning contact-aware robot controllers from mixed integer optimization
… some guarantees of global optimality through mixed-integer programming. That method is applied successfully to a humanoid robot in laboratory conditions, but proves difficult to rely on when the robot is experiences unmodeled disturbances. To overcome those limitations, this thesis also …
-
Advanced mixed-integer programming formulations : methodology, computation, and application
This thesis introduces systematic ways to use mixed-integer programming (MIP) to solve difficult nonconvex optimization problems arising in application areas as varied as operations, robotics, power systems, and machine learning. Our goal is to produce MIP formulations that perform extremely well …
-
Bound tightening to improve branch-and-bound mixed-integer programming
Includes bibliographical references.
-
Polyhedra Study of Mixed Integer Programs With Variable Upper Bounds
We investigate the convex hull of the set defined by a single constraint with continues and binary variables and in addition, variable upper bound constraints are present. We introduce the flow cover inequality, which is valid for a projection. We also give conditions under which this inequality is …
-
Mixed integer linear programming approach for solving assembly scheduling problems
… between operations. It has been formulated as a Mixed Integer Linear Program and is modeled as a flow-like problem. The objective of the problem is to reduce the total makespan (cumulative lead time) of production of final product. In addition to that, move sizes and batch sizes of operations are …
-
Online trajectory planning for UAVs using mixed integer linear programming
… thesis presents a improved path planner using mixed-integer linear programming (MILP) to solve a receding horizon optimization problem for unmanned aerial vehicles (UAV's). Using MILP, hard constraints for obstacle and multi-vehicle avoidance as well as an approximation of vehicle dynamics are …
-
Mixed-integer convex optimization : outer approximation algorithms and modeling power
In this thesis, we study mixed-integer convex optimization, or mixed-integer convex programming (MICP), the class of optimization problems where one seeks to minimize a convex objective function subject to convex constraints and integrality restrictions on a subset of the variables. We focus on two …
-
Advancing mixed-integer programming using data-driven and deduction-based methods
Mixed-Integer Problems (MIPs) form one of the most general classes of optimization problems. As they are used to model many real-world scenarios, solving MIPs efficiently is crucial. Most solvers are based on the well-known Branch-and-Bound algorithm, which utilizes different subroutines to help …
-
Two-Stage Stochastic Mixed Integer Nonlinear Programming: Theory, Algorithms, and Applications
… that allows probabilistic data parameters in mixed integer programming, a well-known tool for optimization modeling with deterministic input data. However, akin to the mixed integer programs, these stochastic models are theoretically intractable and computationally challenging to solve because …
Page 1 of 28