Operations Research

Assortment Planning and Optimization with Reinforcement Learning

/ By / 42 minutes of reading

Executive Summary Retailers face complex decisions in assortment planning – determining the optimal mix of products to stock across stores and channels. Traditional methods struggle to account for changing customer preferences, demand uncertainty, and the myriad factors influencing product performance. Reinforcement Learning (RL) offers a data-driven, dynamic approach to optimize assortments in real time. By […]

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Assortment Planning and Optimization with AI

/ By / 19 minutes of reading

Executive Summary In the rapidly evolving retail landscape, effective assortment planning and optimization are crucial for retailers to meet customer demands, maximize profitability, and maintain a competitive edge. This article presents a comprehensive exploration of an advanced assortment allocation system designed to address the complexities of modern retail. By integrating sophisticated machine learning techniques, modeling

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Leveraging LLMs in Data Science Lifecycle for Demand Forecasting

/ By / 49 minutes of reading

Introduction In the bustling marketplace of modern commerce, navigating the complex currents of demand and supply is akin to a sailor maneuvering through tempestuous seas. The ability to foresee the ebbs and flows of market demand is a lighthouse that guides enterprises safely towards the shores of profitability. However, the lens through which this lighthouse

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A Hypothetical Revenue Management System for Retail & Supply Chain Management

/ By / 8 minutes of reading

Theory Revenue management is the practice of optimizing pricing and inventory in order to maximize profits. In the retail and supply chain industry, effective revenue management can be the difference between success and failure. In this blog post, we will discuss a hypothetical revenue management system that can be used to optimize pricing and inventory

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