Qifang Luo

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In this paper, we proposed an improved cuckoo search optimization (ICS) algorithm for solving planar graph coloring problem. The improved cuckoo search optimization algorithm is consisting of the walking one strategy, swap and inversion strategy and greedy strategy. The proposed improved cuckoo search optimization algorithm can solve the planar graph(More)
In this paper, we propose a novel discrete cuckoo search algorithm (DCS) for solving spherical Traveling Salesman Problem (TSP) where all points are on the surface of a sphere. The algorithm is based on the Lévy flight behaviour and brood parasitic behaviour. The proposed algorithm applies study operator, the " A " operator, and 3-opt operator to solutions(More)
A hybrid particle swarm optimization (HPSO) algorithm, which combines the advantages of Nelder-Mead simplex method (SM) and particle swarm optimization (PSO) algorithm, is put forward to solve systems of nonlinear equations, and it can be used to overcome the difficulty in selecting good initial guess for SM and inaccuracy of PSO due to being easily trapped(More)
The intelligent schedule of vehicles operation is one of the problems which need to be solved in the dispatching system of public transit vehicles, it relates to the development of the city and civic daily life. In this paper, a transit vehicle scheduling optimization algorithm which balancing between the benefits of bus companies and passengers is(More)
A discrete bat algorithm (DBA) is proposed for optimal permutation flow shop scheduling problem (PFSP). Firstly, the discrete bat algorithm is constructed based on the idea of basic bat algorithm, which divide whole scheduling problem into many subscheduling problems and then NEH heuristic be introduced to solve subscheduling problem. Secondly, some(More)
This paper presents a fast-stable population migration algorithm for multi-objective optimization to solve multi-objective optimization problems. Based on the concept of Pareto non-domination and guided by a global optimization experiments, this algorithm adopts dynamic mutation operator and the entire population migrating method to increase the algorithm(More)
In this paper, the application of support vector machine (SVM) approach based on the statistics-learning theory of structural risk minimization in heart disease diagnosis. Aiming at the blindness of man made choice of parameter and kernel function of SVM, a chaotic adaptive particle swarm optimization (CAPSO) method is applied to select parameters of SVM in(More)