Dynamic Optimization for IPS2 Resource Allocation Based on Improved Fuzzy Multiple Linear RegressionReportar como inadecuado




Dynamic Optimization for IPS2 Resource Allocation Based on Improved Fuzzy Multiple Linear Regression - Descarga este documento en PDF. Documentación en PDF para descargar gratis. Disponible también para leer online.

Mathematical Problems in Engineering - Volume 2017 2017, Article ID 2839125, 10 pages - https:-doi.org-10.1155-2017-2839125

Research ArticleSchool of Mechanical Engineering, Shanghai Jiao Tong University, Shanghai, China

Correspondence should be addressed to Maokuan Zheng

Received 5 October 2016; Accepted 12 February 2017; Published 27 February 2017

Academic Editor: Ibrahim Zeid

Copyright © 2017 Maokuan Zheng et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

The study mainly focuses on resource allocation optimization for industrial product-service systems IPS2. The development of IPS2 leads to sustainable economy by introducing cooperative mechanisms apart from commodity transaction. The randomness and fluctuation of service requests from customers lead to the volatility of IPS2 resource utilization ratio. Three basic rules for resource allocation optimization are put forward to improve system operation efficiency and cut unnecessary costs. An approach based on fuzzy multiple linear regression FMLR is developed, which integrates the strength and concision of multiple linear regression in data fitting and factor analysis and the merit of fuzzy theory in dealing with uncertain or vague problems, which helps reduce those costs caused by unnecessary resource transfer. The iteration mechanism is introduced in the FMLR algorithm to improve forecasting accuracy. A case study of human resource allocation optimization in construction machinery industry is implemented to test and verify the proposed model.





Autor: Maokuan Zheng, Xinguo Ming, and Guoming Li

Fuente: https://www.hindawi.com/



DESCARGAR PDF




Documentos relacionados