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Complexity and Algorithms for Optimal Bundle Search Problem with Pairwise Discount

The Journal of Distribution Science / The Journal of Distribution Science, (P)1738-3110; (E)2093-7717
2017, v.15 no.7, pp.35-41
https://doi.org/https://doi.org/10.15722/jds.15.7.201707.35
Chung, Jibok
Choi, Byungcheon
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Abstract

Purpose - A product bundling is a marketing approach where multiple products or components are packaged together into one bundle solution. This paper aims to introduce an optimal bundle search problem (hereinafter called "OBSP") which may be embedded with online recommendation system to provide an optimized service considering pairwise discount and delivery cost. Research design, data, and methodology - Online retailers have their own discount policy and it is time consuming for online shoppers to find an optimal bundle. Unlike an online system recommending one item for each search, the OBSP considers multiple items for each search. We propose a mathematical formulation with numerical example for the OBSP and analyzed the complexity of the problem. Results - We provide two results from the complexity analysis. In general case, the OBSP belongs to strongly NP-Hard which means the difficulty of the problem while the special case of OBSP can be solved within polynomial time by transforming the OBSP into the minimum weighted perfect matching problem. Conclusions - In this paper, we propose the OBSP to provide a customized service considering bundling price and delivery cost. The results of research will be embedded with an online recommendation system to help customers for easy and smart online shopping.

keywords
Internet Shopping Optimization Problem, Bundle Search Problem, Perfect Matching Problem, Online Shopping Recommendation.

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The Journal of Distribution Science