lpsymphony

lpsymphony provides an R interface to the SYMPHONY mixed-integer linear programming (MILP) solver for formulation and solution of MILPs using branch-and-cut and branch-and-price algorithms.

Key Features:

• R interface: Exposes SYMPHONY solver functionality to R for formulation, solution, and inspection of MILP problems.
• Algorithms: Implements branch-and-cut and branch-and-price methods for solving MILPs.
• Parameter customization: Offers extensive solver parameter customizations to adjust solver behavior.
• User-defined callbacks: Supports user-defined callback hooks for custom control during the solve process.
• Compile-time configuration: Provides compile-time configuration options for solver build and behavior.
• Parallel execution support: Supports execution on single-processor, shared-memory, and distributed-memory parallel architectures.
• Operating system compatibility: Runs across major operating systems including Linux, Unix, and Windows.
• Bicriteria optimization: Includes capabilities for bicriteria MILP optimization.
• Warm-start and resume: Supports warm-starting and resuming computations after modifying problem data or solver parameters.
• Persistent cut-pool management: Provides persistent management of cut pools across solver runs.
• Sensitivity analysis: Includes basic MILP sensitivity analysis capabilities.
• Bundled solver source: Contains the complete SYMPHONY solver source code (version 5.6) bundled within the package.

Scientific Applications:

• Bioinformatics optimization: Solving integer and mixed-integer optimization problems arising in bioinformatics workflows.
• Combinatorial search: Addressing combinatorial search problems that require branch-and-bound or branch-and-price strategies.
• Constrained statistical modeling: Enabling constrained statistical modeling and parameter selection that require MILP formulations.
• Domain-specific optimization workflows: Supporting deeply specialized, domain-specific optimization workflows through customizable solver behavior and callbacks.

Methodology:

Uses branch-and-cut and branch-and-price algorithms; supports user-defined callback hooks, extensive parameter and compile-time configuration, parallel execution on single-processor, shared-memory, and distributed-memory architectures, warm-starting and resuming, persistent cut-pool management, and basic MILP sensitivity analysis.