SAS' Varun Valsaraj demonstrates how to build a digital assistant for a warehouse space optimization use case.
SAS' Brandon Reese the EURO Meets NeurIPS 2022 Vehicle Routing Competition, which combined efforts of operations research and machine learning experts.
NeurIPS 2022 allowed researchers and practitioners to share progress and brainstorm new ideas for advancing machine learning and its related fields.
The ultimate objective of a churn model is preventing churn by making a retention offer. To determine reasonable values for profit and loss information, consider the outcomes and the actions that you would take given knowledge of these outcomes. For example, the marketing department of a telecommunications company wants to offer a discount to people who are no longer on a fixed-term contract. To prevent churn, the company is willing to make an offer in exchange for a one-year contract extension.
Machine Learning models are becoming widely used to formulate and describe processes’ key metrics across different industry fields. There is also an increasing need for the integration of these Machine Learning (ML) models with other Advanced Analytics methodologies, such as Optimization. Specifically, in the manufacturing industry, SAS explored state-of-the-art science
Linear programming (LP) and mixed integer linear programming (MILP) solvers are powerful tools. Many real-world business problems, including facility location, production planning, job scheduling, and vehicle routing, naturally lead to linear optimization models. Sometimes a model that is not quite linear can be transformed to an equivalent linear model to reduce
Note from Udo Sglavo on mathematical optimization: When data scientists look at the essence of analytics and wonder about their daily endeavor, it often comes down to supporting better decisions. Peter F. Drucker, the founder of modern management, stated: "Whenever you see a successful business, someone once made a courageous decision."
A good public transportation system is crucial to develop smart cities, particularly in great metropolitan areas. Network optimization algorithms can be applied to better understand urban mobility, particularly based on a multimodal public transportation network.
We will use prescriptive analytics and optimization to select a stock portfolio that maximizes returns while taking risk tolerance into account.
A simple example of how you can combine SAS and open-source technologies to solve real business issues.
