1. ¹University of Tehran, Tehran, Iran
2. ²Iran University of Science and Technology, Tehran, Iran
3. ³Abti-American University of Nigeria, Yola, Nigeria and American University, Washington, DC, USA

Correspondence: R Tavakkoli-Moghaddam, Department of Industrial Engineering and Center of Excellence of Intelligence Based Experimental Mechanics, Faculty of Engineering, University of Tehran, PO Box 11365-4563, Tehran, Iran. E-mail: tavakoli@ut.ac.ir

Received August 2005; Accepted September 2006; Published online 14 February 2007.

Abstract

This paper presents a fuzzy-neural approach for constraint satisfaction of a generalized job shop scheduling problem (GJSSP) fuzzy processing times. Our study is an extension of recently developed research in a GJSSP where the processing time of operations was constant. Our paper assumes that the processing time of jobs is uncertain. The proposed fuzzy-neural approach can be adaptively adjusted with weights of connections based on sequence resource and uncertain processing time constraints of the GJSSP during its processing. The computational results show that the proposed neural approach is able to find good solutions in reasonable time.