Study of optimal site selection for brand promotion based on simulated annealing and genetic algorithms

L. Tong
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Abstract

This article introduces the application of the simulated annealing algorithm (SA) in solving brand promotion problems. The goal of the brand promotion problem is to find a path that minimizes the distance through all cities. We use the SA algorithm to solve the brand promotion problem, which avoids the trap of local optimal solutions by using a randomized search strategy and an acceptance of inferior solutions strategy. In this article, we apply the SA algorithm to a brand promotion problem instance and compare it with genetic algorithms and greedy algorithms. The experimental results show that the SA algorithm can obtain results close to the optimal solution and has better robustness and faster convergence speed.
基于模拟退火和遗传算法的品牌推广最优选址研究
本文介绍了模拟退火算法(SA)在解决品牌推广问题中的应用。品牌推广问题的目标是找到一条通过所有城市的距离最小的路径。我们使用SA算法来解决品牌推广问题,该算法通过使用随机搜索策略和接受劣解策略来避免局部最优解的陷阱。本文将SA算法应用于一个品牌推广问题实例,并与遗传算法和贪心算法进行了比较。实验结果表明,该算法可以得到接近最优解的结果,具有较好的鲁棒性和较快的收敛速度。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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