Study On Multi-objective Optimization Of Pre-drilling Project Based On Immune Genetic Algorithm

In recent years,multi-objective optimization of project management has become a core element of the work,but as a result of the development of engineering and technology,the project become more complex,a number of objectives to achieve balance of pr- oject has become increasingly more difficult.Genetic algorithm(GA),as one of methods to solve such problems has some problems,such as easy to premate, easy to fall into local optimum,local search capability is weak,and the shortcomings is slow.The artiftificial immune algorithm(AIA) introduce the concentration of antibodies of regulatory mechanism to maintain understanding of the diversity of groups, a genetic algorithm to overcome the premature convergence and prone to fall into the shortcomings of local optimum.Therefore,this article based on the theoretical study and experimental analysis of multi-objective genetic algorithm and artiftificial immune algorithm's characteristics, point out a method which base on immune genetic algorithm to solve multi-objective optimization problem.The main contents are as follows:Firstly,the multi-objective optimization problem are described,sum up the theory and processes of current multi-objective optimization algorithm,point out their respective advantages and disadvantages which is used to deal with multi-objective optimization problem.Make a general model of artificial immune algorithm and improve it,which base on distance but not information entropy.Secondly,this paper presents a general immune genetic algorithm model,as while as introduce genetic algorithm in the immune mechanism,design an improved immune genetic algorithm.This algorithm use NSGA's fitness allocation strategies and the introduction of the concept of concentration,in the concentration calculated use the algorithm based on Euclidean distance.Two points crossover operator is used in crosso ver and mutation operator based on the concentration of the adaptive operator,the design of immune operator extracted from the vaccine,vaccination and immune to complete a three-step operation.Through the function tests of searching for multimodal, concluded that the immune genetic algorithm has better global search ability and conve- ver and mutation operator based on the concentration of the adaptive operator,the design of immune operator extracted from the vaccine,vaccination and immune to complete a three-step operation.Through the function tests of searching for multimodal, concluded that the immune genetic algorithm has better global search ability and convergence efficiency.Finally,in order to verify the effect of algorithm to solve practical problems,in this article,use an example of a company whose name is Liaohe Oilfield Great Wall Drilling Company,thougu the application of improved pre-drilling project multi-objective model,use immune genetic algorithm to optimize the problem,and the results analysis verificate that the algorithm in solving practical project on multi-objective optimization problem is effective.