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Exact and heuristic approaches to solve the Internet shopping optimization problem with delivery costs

机译:精确且启发式的方法来解决带有交付成本的互联网购物优化问题

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Internet shopping has been one of the most common online activities, carried out by millions of users every day. As the number of available offers grows, the difficulty in getting the best one among all the shops increases as well. In this paper we propose an integer linear programming (ILP) model and two heuristic solutions, the MinMin algorithm and the cellular processing algorithm, to tackle the Internet shopping optimization problem with delivery costs. The obtained results improve those achieved by the state-of-the-art heuristics, and for small real case scenarios ILP delivers exact solutions in a reasonable amount of time.
机译:互联网购物一直是最常见的在线活动之一,每天都有数百万用户进行。随着可用报价数量的增加,在所有商店中获得最佳报价的难度也随之增加。在本文中,我们提出了一个整数线性规划(ILP)模型和两个启发式解决方案MinMin算法和元胞处理算法,以解决带有交付成本的互联网购物优化问题。所获得的结果改进了通过最新启发式方法获得的结果,并且对于小型实际案例,ILP在合理的时间内提供了精确的解决方案。

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