Category: Learning optimization

I am a person who loves family and science.

Optimizing network software to advance scientific discovery

APRIL 16, 2019 by Ariana Tantillo, Brookhaven National Laboratory High-performance computing (HPC)—the use of supercomputers and parallel processing techniques to solve large computational problems—is of great use in the scientific community. For example, scientists at the U.S. Department of Energy’s (DOE) Brookhaven National Laboratory rely on HPC to analyze the data they collect at the…
Read more

SOLVER TUTORIAL – WHAT MAKES A MODEL HARD TO SOLVE?

On 02 April, 2019 What Makes a Model Hard to Solve? Some optimization models are easy to solve, others are hard. “Hard” models may require a lot of CPU time and random-access memory (RAM) to solve — if they can be solved at all.  The good news is that, with today’s very fast PCs and advanced optimization software from…
Read more

SOLVER TUTORIAL – SIZE, SPARSITY AND INTEGER VARIABLES

On 02 April, 2019 Model Size The size of a solver model is measured by the number of decision variables and the number of constraints it contains. Most optimization software algorithms have a practical upper limit on the size of models they can handle, due to either memory requirements or numerical stability.  Frontline’s standard Solver…
Read more

Manufacturing and process facility trends: Optimization

By MARK T. HOSKE on MARCH 4, 2019Technology update: Optimization is among key trends for manufacturing and process facilities highlighted in the media session at ARC Forum 2019. Courtesy: Mark T. Hoske, Control Engineering, CFE Media Manufacturing and process facilities are taking advantage of trends in optimization to make their applications more efficient, with lower…
Read more

Manufacturing and process facility trends: Optimization

By MARK T. HOSKE on MARCH 4, 2019 Technology update: Optimization is among key trends for manufacturing and process facilities highlighted in the media session at ARC Forum 2019. Courtesy: Mark T. Hoske, Control Engineering, CFE Media Manufacturing and process facilities are taking advantage of trends in optimization to make their applications more efficient, with…
Read more

10 Inventory Management Software Systems for Optimization

March 6, 2019 Retailers are getting smarter by the day, tidying up shelves and aisles with merchandising insights driven by machine learning algorithms. Robots can now optimize inventories at stores with self-service checkouts relaying instant information from the point of sale. Automation goes all the way to the top of the enterprise, with senior managers turning to predictive analytics tools to help them find…
Read more

What Makes a Model Hard to Solve?

Some optimization models are easy to solve, others are hard. “Hard” models may require a lot of CPU time and random-access memory (RAM) to solve — if they can be solved at all.  The good news is that, with today’s very fast PCs and advanced optimization software from Frontline Systems, a very broad range of models can be solved. Three major…
Read more

A new approach for software fault prediction using feature selection

JANUARY 10, 2019 by Ingrid Fadelli , Tech Xplore Researchers at Taif University, Birzeit University and RMIT University have developed a new approach for software fault prediction (SFP), which addresses some of the limitations of existing machine learning SFP techniques. Their approach employs feature selection (FS) to enhance the performance of a layered recurrent neural…
Read more

OPTIMIZATION TUTORIAL – DEFINING CONSTRAINTS

Defining Constraints Constraints are logical conditions that a solution to an optimization problem must satisfy.  They reflect real-world limits on production capacity, market demand, available funds, and so on.  To define a constraint, you first compute the value of interest using the decision variables.  Then you place an appropriate limit (<=, = or >=) on this computed value.  The…
Read more