Accelerating the convergence speed and avoiding the local optimal solution are two main goals of particle swarm optimization（PSO）. The very basic PSO model and some variants of PSO do not consider the enhancement of...Accelerating the convergence speed and avoiding the local optimal solution are two main goals of particle swarm optimization（PSO）. The very basic PSO model and some variants of PSO do not consider the enhancement of the explorative capability of each particle. Thus these methods have a slow convergence speed and may trap into a local optimal solution. To enhance the explorative capability of particles, a scheme called explorative capability enhancement in PSO（ECE-PSO） is proposed by introducing some virtual particles in random directions with random amplitude. The linearly decreasing method related to the maximum iteration and the nonlinearly decreasing method related to the fitness value of the globally best particle are employed to produce virtual particles. The above two methods are thoroughly compared with four representative advanced PSO variants on eight unimodal and multimodal benchmark problems. Experimental results indicate that the convergence speed and solution quality of ECE-PSO outperform the state-of-the-art PSO variants.展开更多
In modern manufacturing pattern, there are many uncertain factors in the modern manufacturing process, such as changes of product attribute, changes of manufacturing resources＇ state, and so on, which cause productio...In modern manufacturing pattern, there are many uncertain factors in the modern manufacturing process, such as changes of product attribute, changes of manufacturing resources＇ state, and so on, which cause production logistics bottleneck frequently shift, and make decisions of production planning and control based on formed bottleneck deviated from practical production process. Considering these factors, present researches mainly apply afterwards control to optimize production process to passively adapt to bottleneck changes If the direction of bottleneck shifting can be accurately forecasted, the transition from afterwards control of chasing bottleneck to beforehand control can be realized. Therefore, aiming at the phenomenon of production logistics bottleneck shifting under uncertain manufacturing circumstances, this paper starts off with dynamic property of capability and requirement and then builds the concepts of bottleneck degree and bottleneck index to describe dynamic bottleneck characteristic of production unit; taken production capability, production load and quality assurance capability into consideration, mathematical model of bottleneck index is established to measure bottleneck degree accurately, consequently, quantitative research on mechanism of production logistics shifting is achieved. Based on bottleneck index, the prediction model of production logistics bottleneck is founded to predict dynamic change of bottleneck accurately. Finally, an example of forecasting and monitoring the production logistics bottleneck in one manufacturing shop is given to testify the validation and practicability of the prediction method.展开更多
基金supported by the Aeronautical Science Fund of Shaanxi Province of China(20145596025)
文摘Accelerating the convergence speed and avoiding the local optimal solution are two main goals of particle swarm optimization（PSO）. The very basic PSO model and some variants of PSO do not consider the enhancement of the explorative capability of each particle. Thus these methods have a slow convergence speed and may trap into a local optimal solution. To enhance the explorative capability of particles, a scheme called explorative capability enhancement in PSO（ECE-PSO） is proposed by introducing some virtual particles in random directions with random amplitude. The linearly decreasing method related to the maximum iteration and the nonlinearly decreasing method related to the fitness value of the globally best particle are employed to produce virtual particles. The above two methods are thoroughly compared with four representative advanced PSO variants on eight unimodal and multimodal benchmark problems. Experimental results indicate that the convergence speed and solution quality of ECE-PSO outperform the state-of-the-art PSO variants.
基金supported by Anhui Provincial Natural Science Foundationof China (Grant No. 090414154)
文摘In modern manufacturing pattern, there are many uncertain factors in the modern manufacturing process, such as changes of product attribute, changes of manufacturing resources＇ state, and so on, which cause production logistics bottleneck frequently shift, and make decisions of production planning and control based on formed bottleneck deviated from practical production process. Considering these factors, present researches mainly apply afterwards control to optimize production process to passively adapt to bottleneck changes If the direction of bottleneck shifting can be accurately forecasted, the transition from afterwards control of chasing bottleneck to beforehand control can be realized. Therefore, aiming at the phenomenon of production logistics bottleneck shifting under uncertain manufacturing circumstances, this paper starts off with dynamic property of capability and requirement and then builds the concepts of bottleneck degree and bottleneck index to describe dynamic bottleneck characteristic of production unit; taken production capability, production load and quality assurance capability into consideration, mathematical model of bottleneck index is established to measure bottleneck degree accurately, consequently, quantitative research on mechanism of production logistics shifting is achieved. Based on bottleneck index, the prediction model of production logistics bottleneck is founded to predict dynamic change of bottleneck accurately. Finally, an example of forecasting and monitoring the production logistics bottleneck in one manufacturing shop is given to testify the validation and practicability of the prediction method.
