Lei Wang; Dunbing Tang

International Journal of Information Technology and Computer Science (IJITCS)

IJITCS Vol. 3, No. 3, 8 Jun. 2011

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Optimization for manufacturing system based on Pheromone

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Author(s)

Lei Wang ^1,* Dunbing Tang ²

1. College of Mechanical & Automotive Engineering, Anhui Polytechnic University, Wuhu, China

2. College of Mechanical and Electrical Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing, China

* Corresponding author.

DOI: https://doi.org/10.5815/ijitcs.2011.03.03

Received: 8 Jul. 2010 / Revised: 20 Nov. 2010 / Accepted: 19 Jan. 2011 / Published: 8 Jun. 2011

Index Terms

Pheromone, Allocation Model, Coordination, Task allocation

Abstract

A new optimization approach, called pheromone, which comes from the collective behavior of ant colonies for food foraging is proposed to optimize task allocation. These ants spread pheromone information and make global information available locally; thus, an ant agent only needs to observe its local environment in order to account for nonlocal concerns in its decisions. This approach has the capacity for task allocation model to automatically find efficient routing paths for processing orders and to reduce communication overhead, which exists in contract net protocol, in shop floor control system. An example confirms that a pheromone-based optimization approach has an excellent allocation performance in shop floor.

Cite This Paper

Lei Wang, Dunbing Tang, "Optimization for manufacturing system based on Pheromone", International Journal of Information Technology and Computer Science(IJITCS), vol.3, vo.3, pp.15-21, 2011. DOI:10.5815/ijitcs.2011.03.03

Reference

[1]W.Xiang,H.P. Lee,“Ant colony intelligence in multi-agent dynamic manufacturing scheduling”,Engineering Applications of Artificial Intelligence,vol.21 pp.73-85,February 2008.

[2]N.G.Hall,C.N.Potts,“Rescheduling for new orders,”Operations Research,vol.52,pp.440-453,June 2004.

[3]D.M.Dilts,N.P.Boyd,and H.H.Whorms,“The evolution of control architectures for automated manufacturing systems,”Journal of Manufacturing System,vol.10,pp.79-93,1991.

[4]N.A.Duffie,R.S.Piper,“Non-hierarchical control of a flexible manufacturing cell,”Robot and Computer Integrated Manufacturing system,vol.3,pp.175-179,1987.

[5]Paulo Leitao, Francisco Restivo,“ADACOR:A holonic architecture for agile and adaptive manufacturing control,”Computers in Industry,vol.57,pp.121-130,February 2006.

[6]C.Ou-Yang,J.S.Lin,“The development ofa hybridhierarchical/heterarchical shop floor control system applying bidding method in job dispatching,”Robotics and Computer-Integrated Manufacturing，vol.14, pp.199-217, June 1998.

[7]P. Peeters, H.V.Brussel, P. Valckenaers, J.Wyns, L. Bongaerts, M. Kollingbaum, and T.Heikkila, “Pheromone based emergent shop floor control system for flexible flow shops,” Artificial Intelligence in Engineering, vol.15, pp. 343-352. October 2001