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.
Motivated by the problem of buying multiple products from different web-stores, REF modeled Internet shopping as an optimization problem, in which a customer wants to buy a list of products from a set of online stores at the minimum final price.
Internet shopping optimization problem
Int. J. Appl. Math. Comput. Sci.
Int. J. Appl. Math. Comput. Sci.
Computer Science