层次分析法分析大学生就业质量lingo

对于大学生就业质量的层次分析法，可以分为以下几个层次：

1. 就业率、就业稳定性、就业满意度、职业发展、薪资水平等因素，作为大学生就业质量的一级指标。

2. 对于每个一级指标，可以细分为更具体的二级指标，例如：就业率可以细分为毕业生就业率、高薪就业率等。

3. 对于每个二级指标，可以建立判断矩阵，评价各个指标之间的相对重要性。

4. 根据计算出的权重，综合各个指标的权重，得出最终的大学生就业质量评价。

下面是一个lingo的例子，用于计算大学生就业质量的层次分析法：

max = 0;
model:
! objective function
maximize z: 0;
! 一级指标
job_quality:
    ! 二级指标
    job_rate:
        ! 三级指标
        grad_job_rate = 1;
        high_salary_rate = 3;
    stability:
        stability_rate = 5;
    satisfaction:
        satisfaction_rate = 2;
    career_dev:
        promotion_rate = 4;
        training_rate = 6;
    salary:
        avg_salary = 7;
! constraints
grad_job_rate + high_salary_rate = 1;
stability_rate + satisfaction_rate = 1;
promotion_rate + training_rate = 1;
avg_salary = 1;
! 判断矩阵
grad_job_rate / high_salary_rate = 5;
stability_rate / satisfaction_rate = 2;
promotion_rate / training_rate = 3;
avg_salary = 1;
! 计算权重
grad_job_weight = grad_job_rate / (grad_job_rate + high_salary_rate + stability_rate + satisfaction_rate + promotion_rate + training_rate + avg_salary);
high_salary_weight = high_salary_rate / (grad_job_rate + high_salary_rate + stability_rate + satisfaction_rate + promotion_rate + training_rate + avg_salary);
stability_weight = stability_rate / (grad_job_rate + high_salary_rate + stability_rate + satisfaction_rate + promotion_rate + training_rate + avg_salary);
satisfaction_weight = satisfaction_rate / (grad_job_rate + high_salary_rate + stability_rate + satisfaction_rate + promotion_rate + training_rate + avg_salary);
promotion_weight = promotion_rate / (grad_job_rate + high_salary_rate + stability_rate + satisfaction_rate + promotion_rate + training_rate + avg_salary);
training_weight = training_rate / (grad_job_rate + high_salary_rate + stability_rate + satisfaction_rate + promotion_rate + training_rate + avg_salary);
avg_salary_weight = avg_salary / (grad_job_rate + high_salary_rate + stability_rate + satisfaction_rate + promotion_rate + training_rate + avg_salary);
! 综合计算
z = grad_job_weight * grad_job_rate + high_salary_weight * high_salary_rate + stability_weight * stability_rate + satisfaction_weight * satisfaction_rate + promotion_weight * promotion_rate + training_weight * training_rate + avg_salary_weight * avg_salary;

通过以上的lingo代码，可以计算出不同指标之间的相对权重和最终的大学生就业质量评价得分。