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Progress in mathematical programming solvers from 2001 to 2020

Thorsten Koch, Timo Berthold, Jaap Pedersen, Charlie Vanaret

2022EURO Journal on Computational Optimization79 citationsDOIOpen Access PDF

Abstract

This study investigates the progress made in lp and milp solver performance during the last two decades by comparing the solver software from the beginning of the millennium with the codes available today. On average, we found out that for solving lp/milp, computer hardware got about 20 times faster, and the algorithms improved by a factor of about nine for lp and around 50 for milp, which gives a total speed-up of about 180 and 1,000 times, respectively. However, these numbers have a very high variance and they considerably underestimate the progress made on the algorithmic side: many problem instances can nowadays be solved within seconds, which the old codes are not able to solve within any reasonable time.

Topics & Concepts

SolverComputer scienceFactor (programming language)Mathematical optimizationSoftwareLinear programmingVariance (accounting)Parallel computingAlgorithmMathematicsProgramming languageAccountingBusinessMetaheuristic Optimization Algorithms ResearchAdvanced Optimization Algorithms ResearchAdvanced Multi-Objective Optimization Algorithms