SAS' Bahar Biller, an operations researcher, details how to develop a supply chain digital twin.
Tag: 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
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 note from Udo Sglavo: This post offers an introduction to complex optimization problems and the sophisticated algorithms SAS provides to solve them. In previous posts of this series, we learned that data availability, combined with more and cheaper computing power, creates an essential opportunity for decision-makers. After looking at network analytics
Public and private schools are struggling to figure out how to bring face-to-face instruction to students during this pandemic. Health risks to students and teachers, parents struggling with child-care options and/or support for virtual learning, and schools’ capacities and budget limitations make this problem a severe logistical challenge. Schools need
The first principle of analytics is about bringing the right analytics technology to the right place at the right time. Whether your data are on-premises, in the cloud, or at the edges of the network – analytics needs to be there with it. Being true to this principle means we
[Nabaruna Karmakar was coauthor of this post] A study was conducted at the University of Denver on The Economic Impacts of the Austin, Texas "No Kill" Resolution. The study found great value in creating an animal welfare-focused community. It highlighted the benefits of economic growth due to an increased need in
Hidden Markov Models Introduction Statistical models of hidden Markov modeling (HMM) have become increasingly popular in the last several years. The models are very rich in mathematical structures and can form the theoretical basis of many real applications. In the classical continuous/discrete Markov process, each state corresponds to an observed
Mathematical optimization can help business leaders make better decisions in every aspect of their business. After a model has been built, end users are usually interested in doing some sort of scenario analysis to test its robustness and visualizing key performance metrics. SAS has various products that can work with
The 2017 edition of SAS Global Forum, the largest annual SAS user group meeting, will be held at the Swan and Dolphin Resort in Orlando, Florida on April 2-5. Among the many analytic talks at SAS Global Forum 2017, several focus on operations research topics like optimization and simulation. If