Geographical Information of Dynamic Carbon Footprints Management System in Orders and Trucks Assignment Problem

Zih Ping Ho

doi:10.4028/www.scientific.net/AMR.518-523.5611

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HomeAdvanced Materials ResearchAdvanced Materials Research Vols. 518-523Geographical Information of Dynamic Carbon...

Geographical Information of Dynamic Carbon Footprints Management System in Orders and Trucks Assignment Problem

Abstract:

A dynamic carbon footprints management system is an important issue in future economics. This research applied geographical information to calculate carbon footprints. It also formulated an orders and trucks assignment problem with capacities of carbon footprints constraints, arrival time constraints and recycling missions constraints to maximize cargoes distribution profits. This study adapted the web based structures for programming, and proposed new approach. After validation, it would increase profits by 46% more than the experience of truck drivers, and profits by 61.5% of that of On Call (individual delivery). If a customer does not attend at a specified place and appointed time, the truck would go back and forward, then consume more gases. Through a web-structure dynamic carbon footprints management system, truck drivers leave ample time to complete their jobs. Future research suggests expanding this research to dynamic routes with consideration of traffic jams.

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Periodical:

Advanced Materials Research (Volumes 518-523)

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5611-5615

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https://doi.org/10.4028/www.scientific.net/AMR.518-523.5611

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Online since:

May 2012

Authors:

Zih Ping Ho

Keywords:

Dynamic Carbon Footprints Management, Geographical Information, Information System, Orders and Trucks Assignment Problem, Trucks Sequencing

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References

[1] G. Hua, T. C. E. Cheng and S. Wang, Managing carbon footprint in inventory management, Int. J. Production Economics. 132 (2011) 178-185.

Google Scholar

[2] S. Cui, H. Niu, W. Wang, G. Zhang, L. Gao and J. Lin, Carbon footprint analysis of the Bus Rapid Transit (BRT) system: a case study of Xiamen City, Int. J. Sustainable Development & World Ecology. 17 (2010) 329-337.

DOI: 10.1080/13504509.2010.490657

Google Scholar

[3] DTLR, The impact of information and communications technologies on travel and freight distribution patterns: Review and assessment of literature, Hopp Association, London, 2002.

Google Scholar

[4] J. B. Edwards, A. C. McKinnon and S. L. Cullinane, Comparative analysis of the carbon footprints of conventional and online retailing, Int. J. of Phy. Distribution & Logistics Mana. 40 (2010) 103-123.

DOI: 10.1108/09600031011018055

Google Scholar

[5] M. Punakivi, Comparing alternative home delivery models for e-grocery business, Ph.D. Dissertation, Helsinki University of Technology, Helsinki, (2003).

Google Scholar

[6] K. Fang, N. Uhan, F. Zhao and J. W. Sutherland, A new approach to scheduling in manufacturing for power consumption and carbon footprint reduction, J. Manufacturing Sys.30 (2011) 234-240.

DOI: 10.1016/j.jmsy.2011.08.004

Google Scholar

[7] H. Krikke, Impact of closed-loop network configurations on carbon footprints: A case study in copiers, Resource, Conservation and Recycling. 55 (2011) 1196-1205.

DOI: 10.1016/j.resconrec.2011.07.001

Google Scholar

[8] A. Chaabane, A. Ramudhin and M. Paquet, Design of sustainable supply chains under the emission trading scheme, Int. J.Production Econo. (2012) 37-49.

DOI: 10.1016/j.ijpe.2010.10.025

Google Scholar

[9] J. Q. Li, D. Borenstein and P. B. Mirchandani, Truck scheduling for solid waste collection in the City of Porto, Omega. 36 (2008) 1133-1149 .

DOI: 10.1016/j.omega.2006.04.007

Google Scholar

[10] Z. P. Ho, An application of new approach for dynamic orders selection to maximize restaurant operational profits, Adv. Mat. Res. J. (Accepted). (2012).

DOI: 10.4028/www.scientific.net/amr.472-475.380

Google Scholar