DocumentCode :
2914834
Title :
Knowledge-based estimation of stockout costs in logistic systems
Author :
Langton, Sebastian ; Geiger, Martin Josef
Author_Institution :
Logistics Manage. Dept., Helmut-Schmidt-Univ., Hamburg, Germany
fYear :
2011
fDate :
22-24 Nov. 2011
Firstpage :
772
Lastpage :
777
Abstract :
The approach introduced in this paper depicts the topic of identification and evaluation of stockout consequences, commonly denoted as stockout cost quantification. Our work is motivated by the limited number of approaches dealing with this problem and, primarily in the field of inventory management, a subsequent need for applicable methods providing reliable stockout cost parameters. We focus on the problem of estimating opportunity costs of stockouts as the most difficult cost component to be determined. Therefore, a method to elicit information by confronting relevant decision makers with representative stockout cases (a priori) is presented. Subsequently, a Genetic Programming (GP) approach for learning opportunity cost functions from these case-based decisions is introduced. It is shown on exemplary tests instances that solutions can be generated which converge to structurally similar opportunity cost functions for representative stockout items. Based on a comparison to benchmarks generated by Neural Networks, it can be concluded that the quality of solutions from the GP algorithm is satisfying.
Keywords :
costing; decision making; genetic algorithms; inventory management; knowledge based systems; logistics; neural nets; production engineering computing; GP algorithm; case-based decisions; decision making; genetic programming approach; inventory management; knowledge-based estimation; learning opportunity cost functions; logistic systems; neural networks; opportunity cost estimation; stockout consequence identification; stockout cost quantification; Artificial neural networks; Benchmark testing; Context; Cost function; Logistics; Reliability; Training; evolutionary computation; genetic programming; knowledge-based systems; neural networks; opportunity costs; stockout costs; stockouts;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Intelligent Systems Design and Applications (ISDA), 2011 11th International Conference on
Conference_Location :
Cordoba
ISSN :
2164-7143
Print_ISBN :
978-1-4577-1676-8
Type :
conf
DOI :
10.1109/ISDA.2011.6121750
Filename :
6121750
Link To Document :
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