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

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.