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Indexed by:期刊论文

Date of Publication:2014-09-01

Journal:ICIC Express Letters

Included Journals:EI、Scopus

Volume:8

Issue:9

Page Number:2545-2550

ISSN No.:1881803X

Abstract:Despite the increasing attentions to supply chain management in construction industry, the study on performance measurement for construction supply chain (CSC) still remains insufficient. Due to fragmented structure and complicated interorganizational relationships, the performance evaluation for CSC is a complex decisionmaking problem. This paper aims to develop an effective supply chain evaluation model containing an index measurement system and an improved evaluation method. A comprehensive performance evaluation index system for CSC is established on the basis of an extended Balanced Score Card framework. The evaluation method is constructed by introducing particle swarm optimization (PSO) algorithm into fuzzy neural network instead of the commonly used evolutionary algorithms. This model can optimize network learning and reasoning by presetting network weights, thresholds, and compensation parameters by PSO. The feasibility of the proposed model is verified through experiments. The results indicate that the PSO-based fuzzy neural network has strong global convergence capability, high generalization precision, and faster convergence rate. The proposed model could contribute to comprehensively evaluating the CSC performance for construction enterprises. ? 2014 ISSN 1881-803X.