Study On Bilateral Matchmaking Method Of Priority In B2B E-commerce

More and more information are becoming available on the internet, there is a growing need for system that can match demands with supplies in an e-marketplace. With the further development of e-commerce, many-to-many e-marketplace will gradually become a mainstream in the future. Matchmaker will play a crucial role to find optimal match, it provides sufficient and flexible service for buyers and suppliers. Therefore, explore on many-to-many matching method is great significance.This thesis proposed a new method to match buyers and suppliers in B2B e-marketplace based on priority and multi-objective optimization. Developed a mathematical model of many-to-many matchmaking system as optimal two objective to solve the multi-attribute matchmaking problem. Attempt using priority based multi-objective genetic algorithm to seek optimal matching solution, and conducted a simulation experiment to verify the proposed matchmaking method. The results of simulation experiment demonstrated the proposed algorithm was flexible. It provided a set of solutions which including multiple optimal match solutions for decision-maker.