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Swarm Intelligence and Bio-Inspired Computation
Tamás VargaAndrás KirályJános Abonyi
其他書名
19. Improvement of PSO Algorithm by Memory-Based Gradient Search—Application in Inventory Management
出版Elsevier Inc. Chapters, 2013-05-16
主題Computers / GeneralTechnology & Engineering / Electronics / DigitalMathematics / AppliedComputers / Data Science / BioinformaticsComputers / Mathematical & Statistical SoftwareTechnology & Engineering / Engineering (General)Technology & Engineering / Electronics / General
ISBN01280690589780128069059
URLhttp://books.google.com.hk/books?id=xz51DAAAQBAJ&hl=&source=gbs_api
EBookSAMPLE
註釋Advanced inventory management in complex supply chains requires effective and robust nonlinear optimization due to the stochastic nature of supply and demand variations. Application of estimated gradients can boost up the convergence of Particle Swarm Optimization (PSO) algorithm but classical gradient calculation cannot be applied to stochastic and uncertain systems. In these situations Monte-Carlo (MC) simulation can be applied to determine the gradient. We developed a memory-based algorithm where instead of generating and evaluating new simulated samples the stored and shared former function evaluations of the particles are sampled to estimate the gradients by local weighted least squares regression. The performance of the resulted regional gradient-based PSO is verified by several benchmark problems and in a complex application example where optimal reorder points of a supply chain are determined.