The author explored estimation by analogy (EBA) as a means of estimating the cost of international freight consignment. A version of the k-Nearest Neighbors algorithm (k-NN) was tested by predicting job costs from a database of over 5000 actual jobs booked by an Irish freight forwarding firm over a seven year period. The effect of a computer intensive training process on overall accuracy of the method was found to be insignificant when the method was implemented with four or fewer neighbors. Overall, the accuracy of the analogy based method, while still significantly less accurate than manually working up estimates, might be worthwhile to implement in practice, depending labor costs in an adopting firm. A simulation model was used to compare manual versus analytical estimation methods. The point of indifference occurs when it takes a firm more than 1.5 worker hours to prepare a manual estimate (at current Irish labor costs). Suggestions are given for future experiments to improve the sampling policy of the method to improve accuracy and to improve overall scalability.
|Advisor:||El Hafsi, Mohsen|
|Commitee:||Goodman, Elodie, Wang, Yunzeng|
|School:||University of California, Riverside|
|School Location:||United States -- California|
|Source:||MAI 53/04M(E), Masters Abstracts International|
|Subjects:||Business administration, Applied Mathematics, Operations research|
|Keywords:||Cost estimation, Estimation by analogy, Freight forwarding, Nearest neighbors, Simulation, Stochastic optimization|
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