Optimizing Online Shopping using Genetic Algorithm

Recent advances in the technology has led to an exponential growth in the e-commerce business. Users today prefer Online Shopping to legacy shopping methods in order to save their effort and time. With the aim of attracting a greater number of customers, the online shopping portals offer products at cheaper rate than offline retailers. The increase in the number of online shopping portals are making it more difficult for the users to purchase a list of products at minimum cost. This can be attributed to the fact that different shopping portals offer different prices for the same product. This problem of obtaining a sequence of products to be procured from different shopping portals with the aim of minimizing the total cost has been termed as the Internet Shopping Optimization Problem. Owing to the NP-hardness of the problem, this paper proposes the application of Genetic Algorithm to solve the Internet Shopping Optimization Problem. Results obtained clearly indicates the efficiency of the proposed work in achieving the optimal solutions in polynomial time.