Seyed hadi Mirghaderi; Akbar Alam Tabriz; Hassan Farsigani,; Farhad Farzad
Volume 13, Issue 38 , October 2015, , Pages 1-25
Abstract
Industrial clusters are one of the new approaches in industrial development of developing countries which has recently attracted the attention of many researchers and policy makers.Clustering has positive economic effects on the region and also increase the competitiveness of the small and medium enterprises ...
Read More
Industrial clusters are one of the new approaches in industrial development of developing countries which has recently attracted the attention of many researchers and policy makers.Clustering has positive economic effects on the region and also increase the competitiveness of the small and medium enterprises (SMEs).But success level of all clusters is not the same because their performances are different. The subject of clusters performance has various aspects and contains a wide range of result areas. This is due to cross-organizational nature and complexity of the internal functions and external effects of cluster as a comprehensive model of industrial cluster performance dimensions have not been presented so far.Precise definition of performance dimensions can reduce (part view) which is based on point of view to clusters and also study of cluster development proceedings with comprehensive approach can be applicable. This study aims to identify the performance dimensions of industrial clusters by classifying the performance measures of industrial clusters and present a model for comprehensive evaluation of industrial clusters performance. For data analysis the method used in this study is cluster analysis which integrated the Classifications of 31 experts used heuristic method and based on that, four performance dimensions of industrial clusters including financial, competitive, economic and environmental along with components and measures of each were extracted.
Soheila Khishtandar; Farhad Farzad; Mostafa Zandieh
Volume 8, Issue 20 , March 2011, , Pages 81-99
Abstract
Different inventory control systems try to determine how much and when to order at the least relevant cost while maintaining a desirable service level for customers. In this article, a continuous review stochastic inventory system, with three objectives, is optimized. In this model, contrary to the traditional ...
Read More
Different inventory control systems try to determine how much and when to order at the least relevant cost while maintaining a desirable service level for customers. In this article, a continuous review stochastic inventory system, with three objectives, is optimized. In this model, contrary to the traditional inventory models, customer service is not considered a shortage cost in the objective function. But the frequency of stock out occasions and the number of items stocked out annually are to be minimized. For determining the Pareto optimal set, multi-objective evolutionary algorithms are used. First, NSGA-II, MOGA, VEGA, RWGA are developed. Then some improvements in NSGA-II mechanisms are made and R-NSGA-II is developed. Subsequently, these algorithms are examined for some criteria such as set coverage and spacing, and the best algorithms for each criteria arc presented. The Result shows that R-NSGA-II has good scores for most criteria. Afterwards, Pareto optimal set is ranked using the method of global criteria.
