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A Study on the Optimization Algorithm for Solving the Supermarket Shopping Path Problem

机译:解决超市购物路径问题的优化算法研究

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Finding shopping path is a key of solving customers who make decision to purchase items and spend time to shopping. The problem of store layout is the length of path for how long a customer walks around in the store. This paper studies the optimization algorithm to apply for solving the supermarket shopping path problem which comparison the popular optimization algorithms which are Genetic algorithm (GA) and Simulated Annealing (SA). The experimental result shows GA has been suitable in solving shopping path both of supermarket where have the single entry-exit door or single entry and multi-exit door. In addition, the processing time of GA is better than SA. The contribution of this study has been discovered as and effective optimization method in evaluating the shopping path for supermarket and consideration the item to allocate shelve planning.
机译:找到购物路径是解决决定购买商品并花时间购物的客户的关键。商店布局的问题是顾客在商店中走动多长时间的路径长度。通过比较遗传算法(GA)和模拟退火算法(SA),研究了适用于解决超市购物路径问题的优化算法。实验结果表明,遗传算法适用于求解具有单进门或单进多出门的超市的购物路径。另外,GA的处理时间比SA好。已经发现这项研究的贡献,是一种有效的优化方法,可用于评估超市的购物路径并考虑分配货架计划的项目。

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