Victor Hugo Nascimento We present a Julia-based interface to the precompiled HALLaR and cuHALLaR binaries for large-scale semidefinite programs (SDPs). Both solvers are established as fast and numerically stable, and accept problem data in formats compatible with SDPA and a new enhanced data format taking advantage of Hybrid Sparse Low-Rank (HSLR) structure. The interface allows users to load … Read more
This paper presents cuHALLaR, a GPU-accelerated solver with an explicit trace constraint \(\mathrm{Tr}(X)\leq \tau^2\), where \(\tau\) is supplied as part of the problem data. The solver is a Julia-based implementation of the hybrid low-rank augmented Lagrangian method, HALLaR, previously proposed by three of the authors. It exploits massive parallelism by performing all core operator evaluations, … Read more
We introduce two new optimization models for the dispatch of ambulances. These models are to our knowledge the first providing a full modelling of the operation of an ambulance fleet, taking into account all or almost all constraints of the problem. The first model, called the ambulance selection problem, is used when an emergency call … Read more