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The job shop scheduling problem (JSSP) is a well known NP-hard problem, and many algorithms have been presented to solve it, but the results are still unsatisfactory. In this paper, a hybrid discrete particle swarm optimization algorithm based on a two layer population structure is proposed to solve the JSSP, meanwhile add an improved simulated annealing(More)
Vehicle routing problem is a well-known NP problem, many heuristic algorithms, such as genetic algorithm, simulated annealing algorithm is applied in the problem. Particle swarm optimization (PSO) is a new evolutionary computation technique. Although PSO algorithm possesses many attractive properties, the method of encoding in NP problem need further to(More)
It is clear that the surface electromyographic-based (sEMG) human-machine interface (HMI) shows a reduction in stability when the muscle fatigue occurs. This paper presents an improved incremental training algorithm that is based on online support vector machine (SVM). The continuous wavelet transform is used to study the changes of sEMG when muscle fatigue(More)
In this paper, an new quantum genetic algorithm (RQGA) is presented to enhance the global optimization capability. Different from previous quantum genetic algorithm, the proposed RQGA uses real-coded replacing binary code, and uses approximation operator replacing rotation gate. RQGA can accelerate the convergence speed, and improve the solution precision.(More)
To improve the global convergence property and the avoidance premature convergence ability of differential evolution (DE), a self-adaptive differential evolution (SDE) was proposed. First, in order to simplify the difficulty of choosing suitable parameter values and improve the ability of breaking away form the local optimum, chaos theory was used to(More)