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数学规划中COPT与Gurobi求解器的对比分析

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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.
Comparative analysis of COPT and Gurobi solvers in mathematical programming
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.

PythonCOPTGurobi solverlinear programmingmixed integer programming

董吉哲、曹建设、周睿延

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长春工业大学电气与电子工程学院,吉林长春 130012

长安大学能源与电气工程学院,陕西西安 710064

Python COPT Gurobi求解器 线性规划 混合整数规划

2024

长春工业大学学报
长春工业大学

长春工业大学学报

影响因子:0.282
ISSN:1674-1374
年,卷(期):2024.45(5)