Research On Magnetotactic Bacteria Optimization Algorithm And Applications

Optimization,especially constrained optimization,is an old and full of new vitality topic and they exist in the field of applications of engineering and scientific.With the intersection and penetration of many different fields of disciplines,people have put forward higher requirements for science and technology,which based on intelligent computation and optimization techniques for the most urgent.Traditional mathematical optimization method because the limitations of their existence has become increasingly difficult to meet the demand of solving optimization problems with high complexity,and bionic intelligence algorithms due to the heuristic optimization strategy shows great development potential in solving many complex constrained optimization problems.Of course,now there is no one algorithm can have the absolute completeness and reliability,therefore,the development of new algorithms to solve the problem is still necessary.Nature has been a source of inspiration of human technology theory and great invention.Many researchers have realized that put the inspiration come from ecological phenomenon into constrained optimization method of intelligent bionic calculation.Magnetotactic bacteria is a kind of prokaryotes which can swimming along the earth's magnetic field line directional in nature.Magnetotactic is a prominent feature of it,by means of the characteristics,bacteria can locate the best oxygen concentration position at maximum efficiency in order to ensure its survival in the surrounding environment.This paper researchs magnetic bacteria optimization algorithm by simulating the biological behavior of bacteria in the process which inspired by this micro-organism behavior which to find the best survival position.After introduced the constrained optimization problem and the knowledges relate to it,magnetic bacteria optimization algorithm is applied to the field of constraint optimization problems' solving.Then analyzed the performance of the algorithm through the comparison of various aspects and validated the superiority of the algorithm.Finally,we apply it to the welded beam,tension/pressure spring and so on engineering constrained optimization examples.The main research contents of this paper are as follows:1.This paper introduces the related concepts,methods and development of improved for solving constrained optimization problems,and also introduces the basic concept of biology of magnetotactic bacteria.Magnetotactic bacteria is prokaryotes swimming along the earth's magnetic field lines direction,and it can seek to the best position with the help of magnetotactic in the surrounding environment.Linear chain formed by the magnetosomes inmagnetotactic bacteria can play a guide role of induced magnetic field,and it is the key to magnetic properties.2.One of the focus of this paper is a new method of magnetic bacteria optimization algorithm's researched,and it also is an innovation.The biological model of magnetotactic bacteria is established in the conditions of the highest efficiency of bacterial movement.The magnetic momentin will come in the form of magnetic performance and the size,shape and number of magnetosomes would affect the magnetic moment.We give the optimization process magnetosome producing magnetic moment corresponding to problem's optimization process,and adjust torque constantly through the cyclic process of magnetosomes' generation,expansion,replacement process to obtain minimum magnetosome torque,finally,to obtain the optimal solution to optimization problem.3.This paper introduces the basic principle of SMES,GA,DE and PSO and 13 common test functions in constrained optimization.Constraint handling methods' selection will affect the performance of algorithm when using evolutionary algorithm for solving constrained optimization problems.Here,we choose Deb's mechanism and then discusses the concrete realization of the process of solving constraint problems.Then analyze its performance properties and compared with the classical algorithms.4.This paper introduces four engineering constrained optimization examples in detail:tension/pressure spring optimization design problem,the welded beam optimization design problem,the pressure vessel optimization design problem and the gear reducer optimization design problem,and they are the optimization problems with constraint condition.Using the magnetic bacteria optimization algorithm do simulation experiment of these problems and then analysis the results.