Improved Artificial Bee Colonal Algorithm And Its Application In E-commerce

Artificial Bee Colony Algorithm(ABC)is a new type of swarm intelligence algorithm,which is based on the the process of all kinds of bees to cooperate to get the best sources.ABC divided bee populations into employee bee,onlooker bee and Scouts bee.Three kinds of bees take turns to detect to find the global optimal solution.The nectar volume of a food source are proportional to the detected possibility of the food source,so it is easy for the bees to stop to exploit the poor food source.Additionally,bee can share the information about food source to others.In conclusion,ABC has its own advantages,but ABC,just like other intelligence algorithm,has some disadvantages such as it's easy to convergence to the local extreme value point and its application should be broaden.This paper improved ABC and researched its application in E-commerce relative problem.The main research work is as follows.(1)Summarize the idea and solving steps of ABC algorithm,introduce the research background of ABC and its application in home and abroad.Summarize the merit and demerit of ABC for the follow-up study.(2)Aiming at the premature convergence problem in artificial bee algorithm,a kind of cellular artificial bee algorithm is proposed,which is based on the principles of cellular automata theory.The evolution rule of cellular and its neighbor are introduced into the algorithm to maintain the bee population's diversity and the algorithm uses evolutionary rule of cellular to avoid local optima.Simulated tests of typical 0-1proramming problem and comparisons with standard ABC and Global-best ABC show the algorithm has fast convergence speed and good global optimization ability.(3)To improve the accuracy and efficiency of the local search,the echolocation mechanisms from the bat algorithm and Natural selection threshold(NST)were introduced to improve ABC algorithm.Improved ABC was used to solve frequency assignment problem.Simulated tests of 21-point frequency assignment problem and comparisons with bat algorithms and standard ABC show that the algorithm had high global convergence speed,high quality of solution and efficiency.(4)Characteristics,protocol and process of multi-agent automated negotiation were introduced.A kind of E-commerce automated negotiation model based on the theory of the ABC algorithm is presented.Based on the multi-Agent and multi-attribute automated negotiation mode,the model integrates the intelligent electronic commerce negotiation techniques.To obtain the solution that maximized the overall interests quickly and accurately,the process of negotiation combined with the process of the ABC algorithm solution.The result of the simulation experiment validate the efficiency of the model.(5)An E-commerce automated negotiation model based on the theory of the ABC algorithm is presented.Based on the multi-Agent and multi-attribute automated negotiation mode,the model integrates the intelligent electronic commerce negotiation techniques.To obtain the solution that maximized the overall interests quickly and accurately,the process of negotiation combined with the process of the ABC algorithm solution.The result of the simulation experiment validate the efficiency of the model.(6)An e-procurement with fuzzy QoS-constraint is built.And an improved artificial bee colony algorithm is developed to solve the model.Based on the existing web procurement mode,the model integrates the non-functional evaluation theory of web service.To obtain the solution that maximized interests quickly and accurately,the theory and process of artificial bee colony algorithm is used to design the solution process of the model.The results of simulation experiments validate the effectiveness of the model.