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Artificial Bee Colony Algorithm Research And Its Application In Vehicle Routing Problems

Posted on:2018-04-12Degree:MasterType:Thesis
Country:ChinaCandidate:M M ZhuFull Text:PDF
GTID:2358330536956296Subject:Computer Science and Technology
Abstract/Summary:PDF Full Text Request
At present,the optimization problems in engineering become more and more difficult,so that traditional solutions cannot solve these problems effectively.These are many common phenomena in our daily life,such as,birds cooperate with each other to forage,ants can find out the sweets in a remote corner,the innocent bee has constructed the most amazing building in the world,and so on.These phenomena are created by some simple organisms,who show the swarm intelligence when they gather together.Human beings are inspired by it and put forward the swarm intelligence algorithm,which includes artificial bee colony(ABC)algorithm.As soon as ABC algorithm appeared,it is studied by more and more researchers because of its simple structure,simple realization and superior performance.Although ABC is excellent,like other optimization algorithms,ABC also suffers from slow convergence.By analyzing the reasons for slow convergence,this thesis proposes a novel artificial bee colony algorithm with local and global information interaction,called ABCLGII.This thesis firstly describes the research background and the development of ABC algorithms.Then,this thesis analyzes the weakness of ABC algorithms and thus deigns ABCLGII.In order to evaluate the performance of ABCLGII,ABCLGII is applied to the numerical optimization problem and vehicle routing problem.The main work in this thesis is listed as follows.1)This thesis analyzes the weaknesses of ABC and proposes a novel artificial bee colony algorithm with local and global information interaction,named ABCLGII.The main innovations of ABCLGII are to enhance the information interaction between the same kinds of bees,and then to exploit the information from some superior solutions to guide the population’s search.Specifically,this mechanism is realized by three novel search equations and an adaptive selection mechanism.By this way,the search behavior of bees is no longer independent and blind,but is cooperative and directional.It improves the global convergence speed,so that the algorithm’s performance is enhanced.After comparing ABCLGII with other ABC variants on 22 scalable benchmark functions,the experimental results show that ABCLGII is better than the compared algorithms on most of test functions.2)This thesis uses ABCLGII to solve vehicle routing problem(VRP).Each individual represents a path by using the discretization approach on all the individuals.Then,ABCLGII evolves iteratively and finds out the best vehicle routing for the purpose of the lowest cost on transportation.By comparing the results of ABC,improved genetic algorithm and ABCLGII in VRP,the advantages of ABCLGII in practical application problems are validated.
Keywords/Search Tags:Artificial Bee Colony, the Numerical Optimization Problem, Vehicle Routing Problem
PDF Full Text Request
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