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arXiv 2007.13414cs.LGcs.AIstat.ML
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超本地化的可持续分类规划

Hyper-local sustainable assortment planning

IBM Research(IBM研究院)

Nupur Aggarwal, Abhishek Bansal, Kushagra Manglik, Kedar Kulkarni, Vikas Raykar

摘要:

对于任何零售商来说,产品组合规划都是一项重要的季节性活动,涉及到选择合适的产品子集在每家商店进行库存。虽然现有的方法只能最大化预期收入,但我们建议通过Higg材料可持续性指数将环境影响也包括在内。收入和环境影响之间的权衡是通过多目标优化方法来平衡的,该方法产生了一个帕累托前沿的最优方案供商家选择。使用所提出的方法在几个产品类别的领先的时装零售商表明,选择具有较低的环境影响,对收入的影响最小的配件是可能的。

英文摘要:

Assortment planning, an important seasonal activity for any retailer, involves choosing the right subset of products to stock in each store.While existing approaches only maximize the expected revenue, we propose including the environmental impact too, through the Higg Material Sustainability Index. The trade-off between revenue and environmental impact is balanced through a multi-objective optimization approach, that yields a Pareto-front of optimal assortments for merchandisers to choose from. Using the proposed approach on a few product categories of a leading fashion retailer shows that choosing assortments with lower environmental impact with a minimal impact on revenue is possible.

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