MindOpt Adapter for CPLEX Benchmarking Performance Analysis
Mou Sun, Tao Li, Wotao Yin
TL;DR
This paper evaluates the effectiveness of the MindOpt Adapter in improving CPLEX 12.9's performance on MIPLIB 2017 benchmarks, showing significant enhancements in problem-solving success and efficiency.
Contribution
It introduces the MindOpt Adapter as a tool that automatically optimizes CPLEX configurations, leading to superior benchmark performance compared to default settings.
Findings
MindOpt Adapter solved 232 of 240 MIPLIB 2017 problems.
It outperformed other solvers in problem-solving success.
It improved geometric mean of solving times.
Abstract
This report provides a comprehensive analysis of the performance of MindOpt Adapter for CPLEX 12.9 in benchmark testing. CPLEX, recognized as a robust Mixed Integer Programming (MIP) solver, has faced some scrutiny regarding its performance on MIPLIB 2017 when configured to default settings. MindOpt Adapter aims to enhance CPLEX's performance by automatically applying improved configurations for solving optimization problems. Our testing demonstrates that MindOpt Adapter for CPLEX yields successfully solved 232 of the 240 problems in the MIPLIB 2017 benchmark set. This performance surpasses all the other solvers in terms of the number of problems solved and the geometric mean of running times. The report provides a comparison of the benchmark results against the outcomes achieved by CPLEX under its default configuration.
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Taxonomy
TopicsParallel Computing and Optimization Techniques · Embedded Systems Design Techniques · Digital Filter Design and Implementation