Customizing ML Predictions for Online Algorithms

Algo’s advanced analytics helps you identify exceptions in product or store performance so you can spend your limited time on the opportunities that offer the most value. Our self-service analysis tools and full-service prescriptive analytics are perfect for enhancing any business workflow. A guessing game and randomized online algorithms.

Analytics predict future demand from historical data on sales, replenishment, and market trends. Insights from operational and supplier data reduce costs and improve GMROI. Store and product clustering, customer segmentation, and anomaly detection simplify planning and mitigate risk. Algo understands the challenge of managing business data spread across manual spreadsheets, databases, and other applications. That’s why we’re here to help create a consistent, accurate representation of your whole supply chain. Spend less time consolidating your information and focus on strategic decision-making and high-impact execution.

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Algo is always at your service. Our friendly virtual assistant helps users find answers to specific sales and inventory questions in seconds. Intuitively discover the precise information you need in the form of instant messages and customized report views. Instantly find and share insights as a business team with one source of truth. Receive proactive alerts as soon as important business metrics change. Look beyond descriptive business intelligence.

The competitive ratio of an online problem is the best competitive ratio achieved by an online algorithm. Note that the final result of an insertion sort is optimum, i.e., a correctly sorted list. For many problems, online algorithms cannot match the performance of offline algorithms.

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This juxtaposition technique can be used anytime you want to compare two similar data structures or algorithms. Our supply chain experts measure their individual performance against the positive business outcomes they create for our customers. By taking an immersive, consultative approach to customer service, our team becomes an organic extension of your team. We apply decades of domain-specific functional and technical experience to customizing our platform in ways that best fit your organization’s needs.

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Finally, this business intelligence needs to be presented in a format that makes it easy for your organization’s cross-functional teams to interpret and act upon. It’s time for you to reimagine planning. Algo’s Demand, Inventory, Replenishment, and Merchandise Planning tools enable you to collaboratively adjust and approve supply chain plans using a flexible, spreadsheet-like layout. View your plans in real time using embedded reports. Our tools are infused with machine learning that simplifies planning at scale.

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If the ratio between the performance of an online algorithm and an optimal offline algorithm is bounded, the online algorithm is called competitive. A problem exemplifying the concepts of online algorithms is the Canadian Traveller Problem. The goal of this problem is to minimize the cost of reaching a target in a weighted graph where some of the edges are unreliable and may have been removed from the graph. However, that an edge has been removed is only revealed to the traveller when she/he reaches one of the edge’s endpoints. The worst case for this problem is simply that all of the unreliable edges fail and the problem reduces to the usual Shortest Path Problem.

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