Research On Particle Swarm Optimization Algorithm For Solving Combinatorial Optimization Problems

Combinatorial optimization problems are typically NP-hard problems,in this paper,based on the improved particle swarm optimization(PSO)algorithms are applied to disorder combinatorial optimization and order combinatorial optimization respectively.The existing improved PSO algorithms have some shortcomings.The current research results are usually suitable to certain scenarios,not pervasive.Due to the randomness of searching optimal solutions,most PSO algorithms cannot guarantee the diversity of the final solution,do not provide the personalized interface,and with the increasing of the particle dimension,the requirements of storage space and computation time will grow exponentially,which will lower the efficiency when solving the high dimensional combinatorial optimization problem.In this paper,for disorder combinatorial optimization problem,we propose a novel chaotic particle swarm optimization algorithm(CS-PSO).By introducing chaos theory in the particle swarm algorithm,we improve the initialization phase and update phase of PSO,using a brand-new set of rules in the initialization and updating phase,enhancing the search efficiency of CS-PSO,achieving the ideal global search capability and adaptability,effectively overcoming the premature problem found frequently in traditional PSO algorithm,and ensuring the diversity of the final combination scheme.The fitness function of CS-PSO introduces the concept of the personalized constraints and general constrains to get a personalized interface,which is used to solve a personalized combination optimization problem.In this paper,for order combinatorial optimization problem,we selected the Web service field of combinatorial optimization as the application scenario.Web service combinatorial optimization is not only a NP problem,also need to consider the logical relationship between service and service,so it is very difficult to find the best web service composition.Based on Web services combinatorial optimization with logical relationship between service and service,we propose chaotic particle swarm optimization algorithm based on the predatory search strategy(PS-CTPSO),by introducing predatory search strategy and cotangent sequence with chaotic characteristics into the particle swarm optimization algorithm,and take the characteristics of Web service into account,making further improvement on the initialization and update phase,and through optimizing the logic relationship between service and service,it is to ensure that the searching efficiency of the algorithm and the diversity of the Web service composition.In the end,in view of the two algorithms,this paper constructs the personalized recommendation system for breakfast(Friend)and best Web service composition recommendation system(BestWS),and through the contrast with the mainstream relevant algorithms,eventually,the experiments show that the recommended combination schemes of this paper is more efficient and reasonable,the algorithms of this paper have the certain application value in the field of combinatorial optimization.