Product Search Algorithm Based on Improved Ant Colony Optimization in a Distributed Network

The crowd intelligence-based e-commerce transaction network (CleTN) is a distributed and unstructured structure. Smart individuals, such as buyers, sellers, third-party organizations, can store information in local nodes connect share via moments. purpose of this study to design product search algorithm on the basis ant colony optimization (ACO) achieve an efficient accurate for demand node network. We introduce improved ideas maximum minimum ants set heuristic algorithms ACO. To reduce blindness, additional relevant factors are selected define calculation equation. pheromone update mechanism integrating into matching factor forwarding probability used rules among algorithm. Finally, facilitated by Java language programming PeerSim software. Experimental results show that has significant advantages over flooding method random walk terms success rate, time, matching, consumption, scalability. introduces idea improving system proposes new equation strategy. effectively.