模拟退火遗传算法求解面试组专家工作安排问题

为了有效求解如何安排面试专家组成员工作使面试公正客观的问题，建立面试安排工作数学模型，该模型为复杂的非线性整数规划问题。提出一种装箱编码、模拟退火遗传、多点交叉、领域搜索变异的遗传算法对数学模型进行求解，并以一个30名专家对300名学生进行面试，且每个面试组4名专家的例子用遗传算法进行求解计算。结果表明，改进后的遗传算法能高效求解出问题的近似最优解，求解结果能满足面试工作安排所提出的要求。

Solving the Interview Group Expert Assignment Problem with Simulated Annealing Genetic Algorithm

In order to effectively solve Arrange fair and objective interview to interview members of the Group, in this pa-per, the issues were discussed, establish its mathematical model, the model is a complex non-linear integer programming problem. Proposed a packing code, simulated annealing genetic, multi-point crossover, the search for variability in the field of genetic algorithms to solve the mathematical model, And with an example： 30 experts to interview 300 students each interview group of four experts, with the genetic algorithm to solve the calculation of the examples, show that the improved genetic algorithm can be efficient for solving the approximate optimal solution of problem solving can meet the job interview fair and reasonable arrangements required to achieve results.