ROUTE FINDING FOR FACILITATING TRANSPORTATION PLANNING TO MAINTAIN SMOOTH PRODUCT FLOW IN SUPPLY CHAIN
Download| Volume 13 Issue 2 2017 | |
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| Author(s): |
Muhammad Ali Memon
Asadullah Shaikh
Kamran Taj Pathan
Majid Hussain Memon
Kamran Dahri
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| Abstract | To gain more profit and market share, manufacturers wish to mobilize as many resources as they can to satisfy every manufacturing order. As Manufacturing is nowadays distributed to several sites, where each site manufactures the intermediate product to assemble the final product Producers, therefore require to transport these products between these sites as well as distribute the final products to faraway customers. Therefore production and transportation planning needs to be coordinated. Manufacturing requires the planning of unmovable resources (machines) with fixed sequences of production routing steps, however, transportation requires the planning of moveable resources (Vehicles). Findings- Each transport request is different from another with a different origin and destination. Hence, it is needed to find the routing (route from origin to destination) of each transport request dynamically. Practical Implications- This paper is dedicated to present a route-finding tool called Path Finder to provide the shortest route by distance or time or both for transportation planning. |
| Keywords | Multi Agent System, Collaborative networks, Transportation planning, Simulation. |
| Year | 2017 |
| Volume | 13 |
| Issue | 2 |
| Type | Short Report |
| Recognized by | Higher Education Commission of Pakistan, HEC | Category | "Y" | Journal Name | IBT Journal of Business Studies | Publisher Name | ILMA University | Jel Classification | D1, D11, D12 | DOI | http://dx.doi.org/10.46745/ilma.jbs.2017.13.02.02 | ISSN no (E, Electronic) | 2409-6520 | ISSN no (P, Print) | 2416-8393 | Country | Pakistan | City | Karachi | Institution Type | University | Journal Type | Open Access | Type of Review | Double Blind Peer Reviewed | Format | Paper Link | http://ibtjbs.ilmauniversity.edu.pk/journal/jbs/13.2/2.pdf | Page | 11-21 | Reference | Li, Y. (2007). Impact of modern logistics on industrial location choice and property markets (Doctoral dissertation, Massachusetts Institute of Technology). Rajagopal, P. (2002). An innovation—diffusion view of implementation of enterprise resource planning (ERP) systems and development of a research model. Information & Management, 40(2), 87-114. Stone, P., & Veloso, M. (2000). Multiagent systems: A survey from a machine learning perspective. Autonomous Robots, 8(3), 345-383. Elwany, H., Shouman, M., & Abou-Ali, 2001 M. Production Scheduling Techniques–A Review. Deparment of Production Engineering, Alexandra University, Alexandra, Egypt. Horenburg, T., Wimmer, J., & Günthner, W. A. (2012). Resource allocation in construction scheduling based on multi-agent negotiation. In Proceedings 14th International Conference on Computing in Civil and Building Engineering. Solar, M., Rojas, J., Mendoza, M., & Monge, R. (2012). A multiagent-based approach to the grid-scheduling problem. CLEI Electronic Journal, 15(2), 2-2. Oprea, M. (2007). MAS_UP-UCT: A multi-agent system for university course timetable scheduling. International Journal of Computers Communications & Control, 2(1), 94-102. Shen, W. (2002). Distributed manufacturing scheduling using intelligent agents. IEEE intelligent systems, 17(1), 88-94. Biggs, N., Lloyd, E. K., & Wilson, R. J. (1976). Graph Theory, 1736-1936. Oxford University Press. Sokas, A. (2011). Algorithms and procedures of determining the shortest route in the graph. In The 7th International Conference TRANSBALTICA, Vilnius, Lithuania. Memon, M. A., Letouzey, A., Karray, M. H., & Archimède, B. (2014). Collaborating Multiple 3PL Enterprises for Ontology-Based Interoperable Transportation Planning. In Enterprise Interoperability VI (pp. 319-329). Springer International Publishing. Memon, M. A., & Archimede, B. (2013, April). Towards a distributed framework for transportation planning: A food supply chain case study. In Networking, Sensing and Control (ICNSC), 2013 10th IEEE International Conference on (pp. 603-608). IEEE. Van der Hoek, W., & Wooldridge, M. (2008). Multi-agent systems. Foundations of Artificial Intelligence, 3, 887-928. Rocha, A. D., Barroca, P., Dal Maso, G., & Oliveira, J. B. (2017). Environment to Simulate Distributed Agent Based Manufacturing Systems. In Service Orientation in Holonic and Multi-Agent Manufacturing (pp. 405-416). Springer, Cham. Khambati, H., Boles, K., & Jetty, P. (2017). Google Maps offers a new way to evaluate claudication. Journal of vascular surgery, 65(5), 1467-1472. |