2016 HiMCM B题特等奖学生论文下载7211

2016 HiMCM B题特等奖学生论文下载7211

 

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论文摘要如下：

Summary A small business, whose main profits are online brick-and-mortar sales, is looking to start its shipping operations. It wishes to provide the continental United States with one-day transit by ground shipping with the United Parcel Service. Our task was to find the optimal warehouse placement to cover the continental United States with one-day transit while minimizing the number of warehouses. After finding the optimal placement, we considered state taxes as well as the tax cuts from the addition of clothing to the company’s inventory.

 

Using transit day maps from the UPS website, we created a genetic algorithm to optimize the coverage of the United States using a certain number of warehouses. We found that it took 32 warehouses to cover 100% of the continental United States with one-day transit. However, this was highly inefficient because it unnecessarily added warehouses in order to provide one-day transit to unpopulated areas like forest preserves. We found that with 23 warehouses, it was possible to cover 95.89% of the continental United States and provide one-day transit to 99.6% of the population, allowing us to cut down on nine warehouses while only losing one-day transit to 0.4% of the population.

 

We then altered our program to take state tax rates into consideration when optimizing the warehouse placement. The new program produced sets containing mostly ZIP codes corresponding to places with low tax rates. However, this greatly reduced the total one-day transit coverage produced by the set of ZIP codes.

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