Network design models logistics

For instance, consider the logistics network design model discussed previously. A DSS is often used to assist in optimizing the number of warehouses required as well as their size and customer allocation to each warehouse. The DSS uses information about the distribution system to calculate the various costs related to the site selection and customer allocation. The data required for this problem involve the manufacturers, warehouses, and customers and the transportation between them. Since this is a long-term planning tool, yearly demand data and costs are typically used, but sometimes the user may need to determine how to account for seasonality. In addition, in order for this kind of DSS to be utilized successfully, the user needs to break the products into product families... 

A multiproduct 4-tier reverse logistics network design model [5, 6]... 

An integrated remanufacturing reverse logistic network design model [11]... 

When applying network design models to the applications of humanitarian and health logistics, there are many unknowns. Getting accurate estimates for these parameters can be quite difficult. The proper quantification of the uncertainty of the model parameters as well as the framework for incorporating the uncertainty into the model is therefore extremely important. For the military humanitarian logistics example, a stochastic optimization approach was used to incorporate probabilistic scenarios. However, additional work is needed in both examples presented, particularly on estimating the "demand"-related parameters. For example, in the health... 

Uster, H., Easwaran, G., Akgali, E., and Cetinkaya, S. Benders decomposition with alternative multiple cuts for a multi-product closed-loop supply chain network design model. Naval Research Logistics 54, no. 8 (2007) 890-907. 

For a scientific discipline such a modular systems development - which is the mathematical basis of farther building of logistics and architecture of distributed networks design and engineering - it is a very important to define the components for a relevant mathematical model. It is well known that the most convenient way to manipulate and compose components is the usage of components with following characteristics of the component [1-3] ... 

Consider the logistics network design problem described in the previous example. For this problem, heuristic approaches as well as optimization based techniques have been developed in the last few years. The choice between heuristics and optimization depends on the complexity of the specific problem as well as on the various modeling issues, such as service level, that the user wishes to consider. For instance, optimization-based techniques may be limited in the size of problem they can handle as well as in the number of parameters and special cases they can consider. Finally, some solvers also combine heuristics and optimization. 

As mentioned earlier, GIS has found application in areas important to supply chain management. These include logistics network design, routing, and mode selection. The idea in all these apphcations is to integrate the GIS with mathematical models and algorithms. Figure 6 provides a schematic representation of such a system. 

An MINLP model for the two-echelon reverse logistics network design [8]... 

Pishvaee, M. S., Jolai, F., and Razmi, J. A stochastic optimization model for integrated forward/reverse logistics network design. Journal of Manufacturing Systems 28, no. 4 (2009) 107-114. 

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