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GALINI: An extensible mixed-integer quadratically-constrained optimization solver

Francesco Ceccon(francesco.ceccon14***at***imperial.ac.uk)
Radu Baltean-Lugojan(radu.baltean-lugojan09***at***imperial.ac.uk)
Michael Lee Bynum(mlbynum***at***sandia.gov)
Chun Li(nickyli98***at***gmail.com)
Ruth Misener(r.misener***at***imperial.ac.uk)

Abstract: We present GALINI, an open source solver for nonconvex mixed-integer quadratically-constrained quadratic programs formulated with the Python algebraic modeling library Pyomo. GALINI uses Pyomo to represent optimization problems and leverages the existing library ecosystem to implement different parts of the solver. GALINI includes a generic branch \& bound algorithm that can be use develop new solvers. The GALINI branch \& cut algorithm can be extended at runtime with new: (i) cutting planes, (ii) branching strategies, (iii) node selection strategies, (iv) primal heuristics, and (v) relaxations. We present computational studies to show GALINI performs comparably to existing open source solvers.

Keywords:

Category 1: Optimization Software and Modeling Systems (Optimization Software Design Principles )

Citation:

Download: [PDF]

Entry Submitted: 01/14/2021
Entry Accepted: 01/14/2021
Entry Last Modified: 01/14/2021

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