Journal
EURO JOURNAL ON COMPUTATIONAL OPTIMIZATION
Volume 10, Issue -, Pages -Publisher
ELSEVIER
DOI: 10.1016/j.ejco.2022.100031
Keywords
LP solver; MILP solver; Mathematical programming software; Benchmark; Mixed Integer Programming
Categories
Funding
- German Federal Ministry of Education and Research (BMBF) [05M14ZAM, 05M20ZBM]
- German Federal Ministry of Economic Affairs and Energy (BMWi) [03EI1004D]
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This study investigates the progress made in LP and MILP solver performance during the last two decades, comparing the solver software from the beginning of the millennium with the codes available today. On average, computer hardware speed for solving LP/MILP increased by about 20 times, and the algorithms improved by a factor of approximately nine for LP and 50 for MILP, resulting in a total speed-up of around 180 and 1,000 times, respectively. However, these numbers vary greatly and significantly underestimate the progress made on the algorithmic side.
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.(c) 2022 The Authors. Published by Elsevier Ltd on behalf of Association of European Operational Research Societies (EURO). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
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