用遗传算法优化超市选址，加速抢占市场份额
Strategies for Resource Allocation of Two Competing Companies using Genetic Algorithm
- 将商场布局建模为二维伊辛模型，用遗传算法搜索最优初始布局
- 数值模拟显示特定拓扑结构的初始布局可更快实现市场主导
- 为竞争企业提供建议：初始布局应具备利于快速扩张的拓扑特性
我们研究大都市中购物中心内商铺的各种战略位置，旨在找出公司在一个竞争环境中取得最终市场份额主导权的最佳策略。该问题以两个竞争超市连锁店在大都市中的情况为背景，采用二维伊辛模型进行描述。通过进化算法对初始配置集合进行编码，并利用蒙特卡洛方法演化模式。数值模拟表明，具有特定拓扑性质的初始模式能更快演变为市场主导状态。本文给出了这些拓扑性质的描述，并就如何设计初始布局以加速向市场主导状态演化提出建议。
原文摘要 · Abstract (English)
We investigate various strategic locations of shops in shopping malls in a metropolis with the aim of finding the best strategy for final dominance of market share by a company in a competing environment. The problem is posed in the context of two competing supermarket chains in a metropolis, described in the framework of the two-dimensional Ising model. Evolutionary Algorithm is used to encode the ensemble of initial configurations and Monte Carlo method is used to evolve the pattern. Numerical simulation indicates that initial patterns with certain topological properties do evolve faster to market dominance. The description of these topological properties is given and suggestions are made on the initial pattern so as to evolve faster to market dominance.
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