Date of Award


Document Type


Degree Name

Doctor of Philosophy (PhD)


Industrial Engineering

Committee Chair/Advisor

Dr. William Ferrell

Committee Member

Dr. Scott Mason

Committee Member

Dr. Amin Khademi

Committee Member

Dr. Tuğçe Işık


The growing amount of freight combined with systemic inefficiencies are stressing current logistic systems. Including horizontal collaboration in the future could provide significant help but this strategy will require several new types of facilities. The most flexible type of horizontal collaboration, however, required freight routing decisions to be made dynamically, in real time, and based on last minute information. This research explores one new facility type operating in this environment that handles a high throughput of pallets or pallet-like containers. A key design feature is how much storage these facilities should have to better coordinate outbound loads. The approach taken here is for a central authority determines at the beginning of each period if pallets, both inbound and currently in storage, should be placed on an outbound truck or held in storage. Pallets can be sent to any destination but, if it is not the correct one, a penalty is assessed. A generalized assignment model is used to determine the decisions that minimize the penalty in a single-period operations. The model is then used to experimentally investigate the impact of the amount of storage. An unexpected result of the experimental study is that the number of pallets sent to storage across many scenarios is described by a Gamma - Poisson distribution. \\ The extensive experimental design using the single-period model provides the insight that the average penalty decreases when the storage capacity increases in an exponential-like pattern. Further, the parameters that affect to the facility performance are statistically analyzed. A factorial design is conducted considering the average penalty as the dependent variable, the number of inbound pallets, the total outbound truck capacity, and the storage capacity as independent factors. When more realistic situations with multiple time periods are considered, the problem becomes a sequence of assignment problems with information from the prior period necessary for making decisions. A dynamic programming formulation is developed to solve the multi-period model. Finally, different policies are evaluated to enhance the efficiency of these facilities.



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