MOSEK Fusion API for Python 11.0.0(BETA)

This manual describes the features of the Fusion API, an object-oriented framework for conic optimization.

• 1 Introduction
  • 1.1 Why the Fusion API for Python?
• 2 Contact Information
• 3 License Agreement
  • 3.1 MOSEK end-user license agreement
  • 3.2 Third party licenses
• 4 Installation
  • 4.1 PIP
  • 4.2 Manual installation
  • 4.3 Testing the Installation
• 5 Design Overview
• 6 Conic Modeling
  • 6.1 The model
  • 6.2 Variables
  • 6.3 Expressions and linear operators
  • 6.4 Constraints and objective
  • 6.5 Matrices
  • 6.6 Parameters
  • 6.7 Stacking and views
  • 6.8 Vectorization
  • 6.9 Reoptimization
• 7 Optimization Tutorials
  • 7.1 Linear Optimization
  • 7.2 Conic Quadratic Optimization
  • 7.3 Power Cone Optimization
  • 7.4 Conic Exponential Optimization
  • 7.5 Geometric Programming
  • 7.6 Semidefinite Optimization
  • 7.7 Integer Optimization
  • 7.8 Disjunctive constraints
  • 7.9 Model Parametrization and Reoptimization
  • 7.10 Problem Modification and Reoptimization
  • 7.11 Parallel optimization
  • 7.12 Retrieving infeasibility certificates
• 8 Solver Interaction Tutorials
  • 8.1 Accessing the solution
  • 8.2 Errors and exceptions
  • 8.3 Input/Output
  • 8.4 Setting solver parameters
  • 8.5 Retrieving information items
  • 8.6 Stopping the solver
  • 8.7 Progress and data callback
  • 8.8 Optimizer API Task
  • 8.9 MOSEK OptServer
• 9 Debugging Tutorials
  • 9.1 Understanding optimizer log
  • 9.2 Addressing numerical issues
  • 9.3 Debugging infeasibility
  • 9.4 Python Console
• 10 Technical guidelines
  • 10.1 Limitations
  • 10.2 Memory management and garbage collection
  • 10.3 Names
  • 10.4 Timing
  • 10.5 Multithreading
  • 10.6 Efficiency
  • 10.7 The license system
  • 10.8 Deployment
• 11 Case Studies
  • 11.1 Portfolio Optimization
  • 11.2 Primal Support-Vector Machine (SVM)
  • 11.3 2D Total Variation
  • 11.4 Multiprocessor Scheduling
  • 11.5 Logistic regression
  • 11.6 Inner and outer Löwner-John Ellipsoids
  • 11.7 SUDOKU
  • 11.8 Travelling Salesman Problem (TSP)
  • 11.9 Nearest Correlation Matrix Problem
  • 11.10 Semidefinite Relaxation of MIQCQO Problems
• 12 Problem Formulation and Solutions
  • 12.1 Linear Optimization
  • 12.2 Conic Optimization
  • 12.3 Semidefinite Optimization
• 13 Optimizers
  • 13.1 Presolve
  • 13.2 Linear Optimization
  • 13.3 Conic Optimization - Interior-point optimizer
  • 13.4 The Optimizer for Mixed-Integer Problems
• 14 Fusion API Reference
  • 14.1 Fusion API conventions
  • 14.2 Pythonic extensions
  • 14.3 Class list
  • 14.4 Parameters grouped by topic
  • 14.5 Parameters (alphabetical list sorted by type)
  • 14.6 Enumerations
  • 14.7 Constants
  • 14.8 Exceptions
  • 14.9 Supported domains
  • 14.10 Class LinAlg
• 15 Supported File Formats
  • 15.1 The LP File Format
  • 15.2 The MPS File Format
  • 15.3 The OPF Format
  • 15.4 The CBF Format
  • 15.5 The PTF Format
  • 15.6 The Task Format
  • 15.7 The JSON Format
  • 15.8 The Solution File Format
• 16 List of examples
• 17 Interface changes
  • 17.1 Important changes compared to version 10
  • 17.2 Changes compared to version 10
• 18 Bibliography