Optimization of RMC Trucks Dispatch Plan Based on Genetic Algorithms and SMS Technique

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How to make the dispatch plan of (Ready-mix concrete) RMC trucks more effective and more efficient is an important issue for the RMC companies. Up to now, only a few researches have been done to solve this problem and almost none of them consider the situation of several RMC plants supplying several job sites. This paper presents a new model, which uses Genetic Algorithms (GAs) to optimize the dispatch plan for several RMC plants supplying several job sites, and use Short Message Service (SMS) technique to monitor the process of going on or to deal with something emergency.

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2194-2199

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September 2011

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© 2012 Trans Tech Publications Ltd. All Rights Reserved

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[1] J. Holland: Adaptation in Natural and Artificial System (University of Michigan Press, USA 1975).

Google Scholar

[2] D.E. Goldberg: Genetic Algorithms in Search, Optimization and Machine Learning (Addition-Wesley, USA 1989).

Google Scholar

[3] M. Gen and R. Cheng: Genetic Algorithms and Engineering Optimization(Wiley, USA 1999).

Google Scholar

[4] C.W. Feng and H.T. Wu: Proceedings of the 17th International Symposium on Automation and Robotics in Construction (Taipei, Taiwan, 2000) p.927– 932.

Google Scholar

[5] D. Naso, M. Surico, B. Turchiano and U. Kaymak: Genetic Algorithms in Supply Chain Scheduling of Ready-Mixed concrete. Erim Report Series Research in Management, (2004).

DOI: 10.1016/j.ejor.2005.12.019

Google Scholar

[6] C.W. Feng and H.T. Wu: Automation in Construction, Vol. 15(2006), p.186~193.

Google Scholar

[7] Nokia, SMS in PDU Mode. (2000).

Google Scholar

[8] SIEMENS, AT Commands for GPRS, (2000).

Google Scholar

[9] GSM07. 07. Information on http: /www. etsi. org.

Google Scholar