Optimization of product bundling strategy decisions and inventory allocation with the integration of the degree of contingency and dead stock levels in a multiple time period setting
College
Gokongwei College of Engineering
Department/Unit
Industrial Engineering
Document Type
Conference Proceeding
Source Title
IEEE International Conference on Industrial Engineering and Engineering Management
Volume
2017-December
First Page
75
Last Page
79
Publication Date
2-9-2018
Abstract
© 2017 IEEE. This paper considers a multiple integer non-linear programming model that aims to optimize the three types of bundling strategies while considering the selection of components for the bundles that integrates the degree of contingency and the dead stock component of the product. The proposed model is validated through different scenarios with varying incremental input parameters in order to determine the effects of the variables to the objective function and the sensitive points in the model. The results were able to show that an increasing degree of contingency is able to affect the pure component variable while the interaction of degree of contingency and the reservation price of a mixed individual appears to have a significant effect on the number of pure bundles. In addition, the dead stock level and degree of contingency have produced adverse effects to bundling optimization. These results have shown that integrating component selection, dead stock level and bundling strategies gave the model the flexibility to change through its varying parameters improving its profitability.
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Digitial Object Identifier (DOI)
10.1109/IEEM.2017.8289854
Recommended Citation
Franco, E., Santos, M., Suyom, D., & Cruz, D. (2018). Optimization of product bundling strategy decisions and inventory allocation with the integration of the degree of contingency and dead stock levels in a multiple time period setting. IEEE International Conference on Industrial Engineering and Engineering Management, 2017-December, 75-79. https://doi.org/10.1109/IEEM.2017.8289854
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