数学规划中COPT与Gurobi求解器的对比分析
Comparative analysis of COPT and Gurobi solvers in mathematical programming
董吉哲 1曹建设 1周睿延2
作者信息
- 1. 长春工业大学电气与电子工程学院,吉林长春 130012
- 2. 长安大学能源与电气工程学院,陕西西安 710064
- 折叠
摘要
在Python语言环境下对国内COPT求解器与国外Gurobi求解器求解线性规划与混合整数规划问题进行测试.每种规划问题采用不同算例进行寻优计算,并结合统计学方法对最优结果及求解时间进行对比分析.结果证明,COPT求解器与Gurobi求解器对两类优化问题的求解精度一致,但COPT求解器对线性规划问题的计算速度快于Gurobi求解器,而在混合整数规划问题上前者慢于后者.
Abstract
Performances of the COPT and Gurobi solvers in linear programming and mixed integer programming are tested on the Python Language.The COPT and Gurobi are used to solve specific examples of different planning problems.The optimal results and computing times are compared and analyzed with statistical methods.It is finally proved that the COPT solver and the Gurobi solver have the same accuracy for both types of optimization problems,but the COPT solver is faster than the Gurobi solver for linear programming problems,while the former is slower than the latter for mixed integer programming problems.
关键词
Python/COPT/Gurobi求解器/线性规划/混合整数规划Key words
Python/COPT/Gurobi solver/linear programming/mixed integer programming引用本文复制引用
出版年
2024
NETL
NSTL
维普
万方数据