The article discusses the InteraSSort framework, designed for interactive assortment planning that encompasses various constraints and product limitations. By utilizing scalable optimization algorithms, the framework aids store planners in determining the optimal product assortment, addressing key questions such as assortment size limits and expected revenues. The assortment planning process includes extensive data collection, choice model selection, and algorithm execution, ultimately facilitating effective communication of decisions among stakeholders. This innovative approach emphasizes the importance of interactivity in deriving optimal solutions for retail environments.
The InteraSSort framework facilitates interactive assortment planning, addressing complex constraints and deep domain knowledge to optimize product selection under various limitations.
Through robust algorithms and scalability, InteraSSort serves to streamline assortment planning, leading to revenue optimization and effective decision-making for store planners.
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