关键词: 非线性混合整数规划, 扩展时间Petri网, 蚁群算法, 遗传算法, 最优路径搜索

Abstract: For the nonlinear mixed integer programming problem with multi-peak objective function and large-scale variables, this paper designs a sequentially selected extended time Petri net (ETPN) model, and proposes its modeling algorithm. This paper also improves the traditional ant colony algorithm and designs partial and overall evolution operators by combining with genetic algorithm, then proposes the optimal searching algorithm based on nonlinear mixed integer programming problem, which solves the evolution problem of both discrete variables and continuous variables, as well as ensures the search range and convergence rate. The result of simulation shows that the new solving algorithm of nonlinear mixed integer programming has better accuracy, universality, stability and high convergence rate, which is suitable for complicated and large-scale questions.

Key words: nonlinear mixed integer programming, extended time Petri net, ant colony algorithm, genetic algorithm, optimization path search