Improved Model of Combinatorial Internet Shopping Optimization Problem Using Evolutionary Algorithms

Online shopping has become an essential part of our life, which provides a suitable, cheap, and quick way for customers to enjoy a wide variety of products. However, due to the large number of online stores, a customer usually faces difficulties to review all available offers manually in order to find a favorite item. The Internet shopping optimization problem (ISOP) is a multiple-item multiple-shop optimization problem, which targets to minimize the total cost for a costumer to purchase a given set of products over all available offers. In this paper, the mathematical model of existing ISOP has been improved. In the improved model of ISOP different constraints and assumptions such as the maximum budget, discounts offered by internet shops have been taken into account. Several metaheuristic optimization methods such as the genetic algorithm are implemented. The obtained numerical results illustrate the effectiveness of the improved model and metaheuristics applied.