Internet shopping optimization problem

Jacek Błażewicz; Mikhail Y. Kovalyov; Jędrzej Musiał; Andrzej P. Urbański; Adam Wojciechowski

International Journal of Applied Mathematics and Computer Science (2010)

  • Volume: 20, Issue: 2, page 385-390
  • ISSN: 1641-876X

Abstract

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A high number of Internet shops makes it difficult for a customer to review manually all the available offers and select optimal outlets for shopping. A partial solution to the problem is brought by price comparators which produce price rankings from collected offers. However, their possibilities are limited to a comparison of offers for a single product requested by the customer. The issue we investigate in this paper is a multiple-item multiple-shop optimization problem, in which total expenses of a customer to buy a given set of items should be minimized over all available offers. In this paper, the Internet Shopping Optimization Problem (ISOP) is defined in a formal way and a proof of its strong NP-hardness is provided. We also describe polynomial time algorithms for special cases of the problem.

How to cite

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Jacek Błażewicz, et al. "Internet shopping optimization problem." International Journal of Applied Mathematics and Computer Science 20.2 (2010): 385-390. <http://eudml.org/doc/207994>.

@article{JacekBłażewicz2010,
abstract = {A high number of Internet shops makes it difficult for a customer to review manually all the available offers and select optimal outlets for shopping. A partial solution to the problem is brought by price comparators which produce price rankings from collected offers. However, their possibilities are limited to a comparison of offers for a single product requested by the customer. The issue we investigate in this paper is a multiple-item multiple-shop optimization problem, in which total expenses of a customer to buy a given set of items should be minimized over all available offers. In this paper, the Internet Shopping Optimization Problem (ISOP) is defined in a formal way and a proof of its strong NP-hardness is provided. We also describe polynomial time algorithms for special cases of the problem.},
author = {Jacek Błażewicz, Mikhail Y. Kovalyov, Jędrzej Musiał, Andrzej P. Urbański, Adam Wojciechowski},
journal = {International Journal of Applied Mathematics and Computer Science},
keywords = {algorithms; computational complexity; combinatorial algorithms; optimization; Internet shopping; internet shopping},
language = {eng},
number = {2},
pages = {385-390},
title = {Internet shopping optimization problem},
url = {http://eudml.org/doc/207994},
volume = {20},
year = {2010},
}

TY - JOUR
AU - Jacek Błażewicz
AU - Mikhail Y. Kovalyov
AU - Jędrzej Musiał
AU - Andrzej P. Urbański
AU - Adam Wojciechowski
TI - Internet shopping optimization problem
JO - International Journal of Applied Mathematics and Computer Science
PY - 2010
VL - 20
IS - 2
SP - 385
EP - 390
AB - A high number of Internet shops makes it difficult for a customer to review manually all the available offers and select optimal outlets for shopping. A partial solution to the problem is brought by price comparators which produce price rankings from collected offers. However, their possibilities are limited to a comparison of offers for a single product requested by the customer. The issue we investigate in this paper is a multiple-item multiple-shop optimization problem, in which total expenses of a customer to buy a given set of items should be minimized over all available offers. In this paper, the Internet Shopping Optimization Problem (ISOP) is defined in a formal way and a proof of its strong NP-hardness is provided. We also describe polynomial time algorithms for special cases of the problem.
LA - eng
KW - algorithms; computational complexity; combinatorial algorithms; optimization; Internet shopping; internet shopping
UR - http://eudml.org/doc/207994
ER -

References

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  1. Crescenzi, P. and Kann, V. (2008). A compendium of NP optimization problems, http://www.nada.kth.se/~viggo/wwwcompendium/. 
  2. Garey, M. and Johnson, D. (1979). Computers and Intractability: A Guide to the Theory of NP-Completeness, Freeman, New York, NY. Zbl0411.68039
  3. Gemius, S. (2008). E-commerce in Poland, http://gemius.pl/pl/raporty/2008-06/03. 
  4. Horrigan, J. (2008), On-line Shopping, Pew Research Center, http://www.pewinternet.org/~/media//Files/Reports/2008/PIP_Onlinepping.pdf.pdf. 
  5. Klein, S. (2000). The emergence of auctions on the world wide web, in M. Shaw, R. Blanning, T. Strader and A. Whinston (Eds.), Handbook on Electronic Commerce, Springer-Verlag, Berlin/Heidelberg, pp. 627-645. 
  6. Langdon, C., Roghe, F. and Shaw, M. (2000). Consumer mass market on-line payment solutions, in M. Shaw, R. Blanning, T. Strader and A. Whinston (Eds.), Handbook on Electronic Commerce, Springer-Verlag, Berlin/Heidelberg, pp. 273-288. 
  7. Lee, H. (1998). Do electronic marketplaces lower the prices of goods?, Communications of the ACM 41(1): 73-80. 
  8. Lesk, M. (1997). Practical Digital Libraries: Books, Bytes and Bucks, Morgan Kaufmann Publishers, San Francisco, CA. 
  9. Liang, T. and Huang, J. (1998). An empirical study on consumer acceptance of products in electronic markets: A transactional cost model, Decision Support Systems 21(1): 29-43. 
  10. Musiał, J. and Wojciechowski, A. (2009). A customer assistance system: Optimizing basket cost, Foundations of Computing and Decision Sciences 34(1): 59-69. 
  11. Raz, R. and Safra, S. (1997). A sub-constant error-probability low-degree test, and sub-constant error-probability PCP characterization of NP, 29th Annual ACM Symposium on Theory of Computing, El Paso, TX, USA, pp. 475-484. Zbl0963.68175
  12. Satzger, B., Endres, M. and Kielssing, W. (2006). A preferencebased recommender system, in K. Bauknecht, B. Pröll and H. Werthner (Eds.), E-Commerce and Web Technologies, Lecture Notes in Computer Science, Vol. 4082, Springer-Verlag, Berlin/Heidelberg, pp. 31-40. 
  13. Tolle, K. and Chen, H. (2000). Intelligent software agents for electronic commerce, in M. Shaw, R. Blanning, T. Strader and A. Whinston (Eds.), Handbook on Electronic Commerce, Springer-Verlag, Berlin/Heidelberg, pp. 265-382. 
  14. Vulkan, N. (2003). The Economics of E-Commerce. A Strategic Guide to Understanding and Designing the On-line Marketplace, Princeton University Press, Princeton, NJ. 

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