数学建模竞赛论文评审优化协商方案

In view of problem 1,firstly,a negotiation graph is constructed by using data information,the thesis negotiation allocation problem is transformed into the maximum edge covering problem of the negotiation graph,a nonlinear integer optimization model is established,and a genetic algorithm is used to solve the model,so as to obtain the optimal negotiation allocation scheme.The whole negotiation process takes only 28 min.To question 2,considering the differences between different teachers consultation work size,diagram,constructs the weighted negotiation will negotiate to quota as negotiation between teacher diagram edge weights,in each round of iteration process,dynamic update consultation of edge weights in the diagram,the dynamic constraint objective optimization model was established,and used to solve the optimization equation of particle swarm optimization(pso),teacher strangers in consultation,negotiation scheme,for the best,the whole scheme takes only56 min.For question 3,in view of the three teachers of special circumstances,the whole thesis negotiation assignment problem into subproblems multiple negotiation,construct the objective optimization model,step by step so as to form a constrained multi-objective optimization modelof multi-objective genetic optimization algorithm,and proposes the iteration by calculation,solving about the optimal distribution plan for the negotiation,under the condition of the whole negotiation process takes 64 min,in line with the three teachers demand should be negotiated before comes to end.Key words nonlinear integer optimization multi-objective constraint genetic algorithmmaximum edge covering paper negotiation allocatio