Please use this identifier to cite or link to this item: https://doi.org/10.1016/j.engappai.2007.03.008
Title: Ant colony intelligence in multi-agent dynamic manufacturing scheduling
Authors: Xiang, W.
Lee, H.P. 
Keywords: Ant colony intelligence
Contract-net protocol
Dispatching rules
Dynamic scheduling
Multi-agent system
Task allocating
Task sequencing
Issue Date: Feb-2008
Source: Xiang, W., Lee, H.P. (2008-02). Ant colony intelligence in multi-agent dynamic manufacturing scheduling. Engineering Applications of Artificial Intelligence 21 (1) : 73-85. ScholarBank@NUS Repository. https://doi.org/10.1016/j.engappai.2007.03.008
Abstract: This study aims at building an efficient agent-based dynamic scheduling for real-world manufacturing systems with various products, processes, and disturbances. Ant colony intelligence (ACI) is proposed to be combined with local agent coordination so as to make autonomous agents adaptive to changing circumstances and to give rise to efficient global performance. The work here differs from other dynamic scheduling research in two areas: (1) a more generic and realistic manufacturing model with multiple product types, multiple/parallel multi-purpose machines with sequence-dependent setup constraints, and various dynamic disturbances is used, (2) ACI integrated with both machine agents and job agents to solve not only the task allocation problem, but also the task sequencing problem. The implementation of the aforementioned issues in a multi-agent system (MAS) is discussed. Simulation results show that, for most of the performance measures, a MAS integrated with well-designed ant-inspired coordination performs well compared to a MAS using dispatching rules. © 2007 Elsevier Ltd. All rights reserved.
Source Title: Engineering Applications of Artificial Intelligence
URI: http://scholarbank.nus.edu.sg/handle/10635/59544
ISSN: 09521976
DOI: 10.1016/j.engappai.2007.03.008
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