Parameter Optimization and Simulation in Implementing Integrated Marketing Communications

This paper is aimed at applying genetic algorithm to solve the optimization problem of resources investment ratio in the integrated marketing communications process. In order to achieve benefits optimization, it is advisable to allocate invested resources to various marketing communications. This is a process of optimization decision-making. In the process, to achieve optimal benefits, a parameter optimization model of integrated marketing communications is firstly established with marketing demands, resources allocation and propagation ability as its constraint condition. Then, an optimal result is intended to obtain by selection, crossover and mutation of genetic algorithm. In selection operation, conditioned optimal retention strategy is applied; in crossover operation, lineal crossing is applied; in mutation operation, crossover probability and mutation probability are dynamically adjusted. The simulation result indicates that the growth rate of total utility after optimization has reached 24.06%, and a parameter optimization in IMC has been achieved. As a result, it provides strong decision support for the implementation of marketing communications.