Search Results: SAS Optimization (596)

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Subbu Pazhani 0
Simulated Annealing (SA) Metaheuristic in SAS Optimization

Authors: Subbu Pazhani and Rob Pratt Large-scale real-world optimization problems with advanced business rules are often difficult to solve with standalone traditional optimization algorithms. Metaheuristic algorithms often complement these traditional optimization techniques. These are a class of powerful and flexible algorithms designed to address complex optimization problems, which traditional methods

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Automated linearization in SAS Optimization

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

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Patricia Neri 0
Solving Sudoku puzzles using Constraint Programming in SAS Optimization

Most people who work with optimization are familiar with Linear and Integer Programming, to their toolkit they could add Constraint Programming. Constraint Programming is a powerful technique that is used to solve powerful “real-world” problems in a variety of areas, such as, planning, scheduling, DNA Sequencing, computer graphics and natural

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Mathematical optimization at SAS

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."

Analytics | Programming Tips
Rick Wicklin 0
Quadratic optimization in SAS

At SAS Global Forum last week, I saw a poster that used SAS/IML to optimized a quadratic objective function that arises in financial portfolio management (Xia, Eberhardt, and Kastin, 2017). The authors used the Newton-Raphson optimizer (NLPNRA routine) in SAS/IML to optimize a hypothetical portfolio of assets. The Newton-Raphson algorithm

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Alexandru Bobe 0
Real-time computer vision for worker safety using SAS Event Stream Processing

In high-risk industries like construction and manufacturing, worker safety isn’t just a priority; it’s a constant challenge. Fast-moving environments, heavy machinery, and human unpredictability make it incredibly tough to monitor compliance and catch dangerous behavior before it leads to injury. As data scientists, we wanted to tackle that challenge head-on.

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Bahar Biller 0
Optimize spare parts inventory under uncertainty with SAS: A simulation-based approach

Authors: Bahar Biller, Jagdishwar Mankala, and Jinxin Yi Managing spare parts inventory is a critical aspect of asset performance management, especially in industries where equipment downtime is costly. This post, based on a real-world project with a major aircraft manufacturer, explores how to optimize spare parts inventory under uncertainty. We

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