params.m
函数参数(文件名)% 2023年版权,Gurobi优化,LLC % %使用参数模型。狗万app足彩% %几秒钟的MIP解决不同的参数。%的选择MIP差距最小,优化%是恢复,直到找到最优解。%读取流模型(“% s \ n阅读模式”,文件名);模型= gurobi_read(文件名);实例变量=找到(模型。vtype ~ = ' C ');如果长度(实例变量)< = 0流(”模型的所有变量是连续的,无关\ n”);返回;%设置2次极限参数。期限= 2;%现在解决MIPFocus模型与不同的值的参数。MIPFocus = 0; result = gurobi(model, params); bestgap = result.mipgap; bestparams = params; for i = 1:3 params.MIPFocus = i; result = gurobi(model, params); if result.mipgap < bestgap bestparams = params; bestgap = result.mipgap; end end % Finally, reset the time limit and Re-solve model to optimality bestparams.TimeLimit = Inf; result = gurobi(model, bestparams); fprintf('Solution status: %s, objective value %g\n', ... result.status, result.objval); end
