A Hybrid Ant Colony Algorithm For The P-median Problem

With the rapid development of the logistics modernization economy,the social transportation road information is getting higher and higher,and the realization of the optimal selection plays an important role in the modern urban planning.The location of reasonable facilities has great influence on the distribution service level,cost and benefit.The location of reasonable facilities is an important research subject in the field of facility location.The P-medium problem is one of the types of facility location,and it is also the focus of current research.Modern intelligent optimization algorithms include tabu search algorithm,simulated annealing algorithm,ant colony algorithm,immune optimization algorithm and so on.The emergence of these algorithms provides new tools for solving facility location problem.P-median problem is complex and belongs to NP-hard problem.This paper studies the construction of P-median problem model,and proposes a hybrid optimization algorithm based on ant colony algorithm and immune optimization algorithm for facility location optimization problem.Aiming at the imperfection of ant colony algorithm,through the immune optimization algorithm to dispose initial solution of ant colony algorithm and selection of pheromone updating strategy,at the beginning of the optimization process,stochastic optimization using ant colony algorithm to expand search range of solution;it takes a long time for the ant colony algorithm to seek solution and easily to stagnate,so it uses immune optimization algorithm to jump out of the local the optimal solution and enhance algorithm traversal optimization ability to improve the calculation speed of the ant colony algorithm.It has been proved by many experiments,the optimal location of the facility can be achieved by using the hybrid optimization algorithm,and the optimal solution or the approximate optimal solution can be obtained efficiently and quickly.The reference data in the data base as an example,calculation procedure was programmed using MATLAB language.To evaluate validity of our proposed algorithm,the performance of our algorithms was tested.At the same time,the verification of our algorithms for the uncapacitated facility location problem was tested on benchmark from OR the library,the results show that the hybrid algorithm has the superiority compared with other single intelligent algorithm.Moreover,the parameters of the hybrid intelligent algorithm are compared and analyzed,and the optimal combination of the parameters is discussed.