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http://hdl.handle.net/10057/1391
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| Title: | Uncertain location routing problem (LRP) integrated to inventory considering space limitation |
| Authors: | Sajjadi, Seyed Reza
Cheraghi, S. Hossein |
| Issue Date: | 25-Apr-2008 |
| Publisher: | Wichita State University. Graduate School. |
| Citation: | Sajjadi, Reza S., Cheraghi, Hossein S. (2008). Uncertain location routing problem (LRP) integrated to inventory considering space limitation. In Proceedings: 4th Annual Symposium: Graduate Research and Scholarly Projects. Wichita, KS: Wichita State University, p.125-126 |
| Series/Report no.: | GRASP
v.4 |
| Abstract: | An optimal supply chain management system has a direct effect on the performance of any enterprise and could
result in substantial cost savings. Successful supply chain management involves many decisions relating to the flow of the
products. The decisions fall into three levels: strategic, tactical, and operational differentiated depending on the time horizon
during which the decisions are made. Since decisions at these three levels are interdependent, optimizing at individual levels
will lead to sub-optimal solution for the network. In this study, location as a strategic decision is combined with two tactical
decisions: routing and inventory. First, location and routing decisions are combined to form location-routing problem (LRP).
LRP can be defined as solving the following three sub- problems at the same time: locating one or more plants and
warehouses among a set of potential plants and warehouses, assigning customers to selected depots, and determining routes
from selected depots to assigned customers to minimize the cost of the supply network. Then, to make further improvements
in the network, it is proposed to integrate an inventory model under the fixed interval order policy to the LRP. Since in the
real world application, warehouses are limited by space capacity, a third logistic party copes with the space limitation if
needed. Moreover, it is assumed that customers demand their multi- products requirement under stochastic condition. To
solve such a model a heuristic solution is proposed. |
| Description: | Paper presented to the 4th Annual Symposium on Graduate Research and Scholarly Projects (GRASP) held at the Hughes Metropolitan Complex, Wichita State University, April 25, 2008.
Research completed at the Department of Industrial and Manufacturing Engineering, College of Engineering |
| URI: | http://hdl.handle.net/10057/1391 |
| Appears in Collections: | IME Graduate Student Conference Papers
Proceedings: 4th Annual Symposium: Graduate Research and Scholarly Projects
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| grasp-2008-59.pdf | Article | 180Kb | Adobe PDF | View/Open |
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