Automated Solution to Calculate an Optimal filling of Retail Space
Challenge: Optimization of Retail Space: We have a certain number of shelves in a store and various display zones that must be represented. The task is to fill the shelves in such a way that the chosen layout is maximally effective in terms of revenue and also meets business requirements.
Solution: I wrote a library in Python that, based on sales data and store size, calculates how the retail space should be filled. It utilizes a Beam Search algorithm that, at each step, retains not just one best solution, but the top N solutions. This approach allows for diversity (as the best solution at each step does not always yield the best sequence) and maintains a reasonable breadth of search by not analyzing very poor filling options. This solution is automated, simplifying its use for business representatives.
Outcome: This solution will be used for zoning in the deployment of new stores and the redesign of old ones
About expert
A Data Analyst at Magnit Tech.
Vladislav applied their knowledge of Data analysis and Business analysis in FoodTech on the following markets: Russia.
Vladislav built products like Internal service using the variety of tools such as tool Jira, Confluence and Tableau.
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