Particle Swarm Optimization for Correlative Product Combinatorial Introduction Model

摘要

Enterprises need to develop a process to determine how to find and develop new product ideas and finally, how to successfully introduce them to the marketplace. To address this problem, conceptions of Optimal Introduction Period and Correlative Profit were presented. Based on the quantitative description of the product life cycle, a Non-Linear Semi-Infinite Programming model of new product introduction was proposed. The proposed model was solved by improved Particle Swarm Optimization (PSO) algorithms. Optimal solution of the given example shows that Particle Swarm Optimization has become the hotspot of evolutionary computation because of its excellent performance and simplicity for implement in solving combined optimization problems.