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.
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Showing 1 to 20 of 20 for “"Mixed Integer Programming-MIP"”.
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ESSAYS ON OPTIMIZATION AND SUPPLY CHAIN STRATEGIES FOR SUSTAINABLE SYSTEMS: INSIGHTS FROM FRACTAL DIMENSION IMAGE ANALYSIS, PHOTOVOLTAIC MANUFACTURING RESILIENCE, AND FRESH PRODUCE INFRASTRUCTURE
… with decarbonization; and (iii) a large-scale mixed-integer programming (MIP) model for locating and sizing fresh-produce hubs to support regional food security and cost-effective distribution. Together, these essays illustrate how reproducible analytics and optimization can inform resilient, …
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Discrete Approximations, Relaxations, and Applications in Quadratically Constrained Quadratic Programming
We present works on theory and applications for Mixed Integer Quadratically Constrained Quadratic Programs (MIQCQP). We introduce new mixed integer programming (MIP)-based relaxation and approximation schemes for general Quadratically Constrained Quadratic Programs (QCQP's), and also study …
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Temporal Bandwidth-Intensive Virtual Network Allocation Optimization in Data Centers
… demand requests. For this problem, we present a mixed-integer programming (MIP) problem formulation where any request from a VN customer may be assigned to any virtual machine so that network resource availability is optimized. We present an overbooking strategy that may be employed to allow for …
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Methods for Generating Alternative Solutions to Environmental Planning Problems
… waste problem, which are formulated as linear programming models, and a wastewater treatment system planning problem, which is formulated as a mixed integer programming (MIP) model. The results show that various attractive and different plans for the problems can be obtained by using the above …
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Path planning of Autonomous Underwater Vehicles for adaptive sampling
… two methods are developed to solve it based on Mixed Integer Programming (MIP). The first method is predicated on network-flow ideas and is shown to have similarities to the Selective Traveling Salesman Problem. An important classification of the set of path-planning problems to be solved is the …
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Data-driven optimization for police beat design in South Fulton, Georgia
… this, we formulate the optimal beat design as a mixed-integer programming (MIP) program with contiguity and compactness constraints on the shape of the beats. The optimization problem is solved using simulated annealing due to its large-scale and non-convex nature. Our resulted beat design can …
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Statistical Learning with Discrete Structures: Statistical and Computational Perspectives
… computationally friendlier estimators based on Mixed Integer Programming (MIP) under suitable statistical assumptions. We study the statistical and computational properties of our estimators. In the fourth chapter, we study the multi-task learning problem with sparse linear estimators. Motivated …
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Optimization Methods for Machine Learning under Structural Constraints
… Branch-and-Bound (BnB) framework that solves a mixed integer programming (MIP) formulation of the proposed estimator. Our estimator is computationally scalable to p~10,000, and provides faster runtime compared to competing ℓ₁ approaches, while leading to superior statistical performance. In the …
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Optimizing In-Garage Charging Schedules to Maximize Electrified Mileage for Electric Bus Fleets
… temperature, ridership, and speeds. The proposed mixed-integer programming (MIP) model maximizes total electrified mileage while considering constraints related to charger configuration, block schedules, energy requirements, and battery capacity. To solve this complex problem in a reasonable …
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Supply chain optimization : formulations and algorithms
… network design problems. We develop mathematical programming formulations, heuristic algorithms, and enhanced algorithms using approximate dynamic programming (ADP). We achieve a strong mixed integer programming (MIP) formulation, and fast, reliable algorithms, which can be extended to problems …
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Multidisciplinary Design Optimization of Composite Spacecraft Structures using Lamination Parameters and Integer Programming
… of black-box global optimization algorithms and Mixed Integer Programming (MIP)-based optimization techniques developed in this work. Lamination parameters and MIP are adopted to optimize composite panels efficiently. The framework integrates structural, thermal and acoustic analysis to optimize …
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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 …
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Semidefinite Cuts and Partial Convexification Techniques with Applications to Continuous Nonconvex Optimization, Stochastic Integer Programming, and Facility Layout Problems
… alone. We then narrow our focus to the class of mixed-integer programming (MIP) problems, and develop a modification of Benders' decomposition method using concepts from RLT and lift-and-project cuts. This method is particularly motivated by the class of two-stage stochastic programs with integer …
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Intelligent Digital Twin for Optimizing Warehouse Operations: Embedded Optimization Components for Enhanced Order-Picking Efficiency
… process. Optimization models are developed using mixed integer programming (MIP) techniques. The DOB combines heuristic and mixed integer linear programming (MILP) models, with feasibility assessed by a CP-SAT solver. Near-optimal picking tours are derived from the Travelling Salesman Problem …
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Sparse Learning using Discrete Optimization: Scalable Algorithms and Statistical Insights
… branch-and-bound (BnB) framework that solves a mixed integer programming (MIP) formulation of the problem. In a radical shift from modern MIP solvers, we solve the BnB subproblems using a specialized first-order method that exploits sparsity. Our open-source solver L0BnB can scale to instances …
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Foundations of fuzzy answer set programming
Answer set programming (ASP) is a declarative language that is tailored towards combinatorial search problems. Although ASP has been applied to many problems, such as planning, configuration and verification of software, and database repair, it is less suitable for describing continuous problems. …
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Integrated Scheduling and Material Handling: Theory and Applications in Manufacturing Systems
… under battery constraints, proposing a novel mixed-integer programming formulation and an exact solution approach based on logic-based Benders decomposition. Third, it extends integrated models to a buffer-constrained flow shop setting with mobile buffering, introducing a decomposition-based …
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Detection and Localization of Pressure Transients in Water Distribution Systems
… number of sensors are available, we formulate a mixed-integer programming (MIP) optimization model and employ a genetic algorithm to find solutions. The second problem involves determining the minimum number of sensors and their optimal locations to detect transient events across the entire …
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A Sequence-Pair and Mixed Integer Programming Based Methodology for the Facility Layout Problem
… of this research is based on a methodology of mixed integer programming (MIP) models. However, these MIP-FLP models can only solve problems with a limited number of departments to optimality due to a large number of binary variables used in the models to prevent departments from overlapping. …
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Nondifferentiable Optimization of Lagrangian Dual Formulations for Linear Programs with Recovery of Primal Solutions
… with solving large-scale, ill-structured linear programming (LP) problems via Lagrangian dual (LD) reformulations. A principal motivation for this work arises in the context of solving mixed-integer programming (MIP) problems where LP relaxations, sometimes in higher dimensional spaces, are …