Industry News

AIMMS, UniSoma, CAT Squared form global partnership

AIMMS, a vendor of prescriptive analytics software, and UniSoma, a provider of advanced planning solutions, announced a global partnership with CAT Squared, a company that specializes in innovative software solutions designed specifically for the food industry. The partnership will enable AIMMS, UniSoma and CAT Squared to provide prescriptive analytics applications for food processing and production companies.

CAT Squared customers include leading enterprises in beef, pork, chicken, turkey, seafood and produce processing and handling. These companies are already collecting real-time data from the plant floor and are equipped with real-time reporting for production and inventory and farm-to-fork traceability.

UniSoma’s expert consultants are experienced at working with global companies in the food industry as well. UniSoma has been a longtime AIMMS partner. Through their partnership, the companies have enabled food industry giants like Marfrig and JBS to develop planning that generate significant business value.

The initial solution developed through this new partnership will be a tactical planning application for customers that use CAT Squared solutions to monitor and manage data. The AIMMS PRO platform and CAT Squared’s software suite will be tightly integrated to empower customers with a better planning tool. Supported by UniSoma’s knowledge in optimization models and in leveraging existing data, these companies will be better equipped to overcome barriers in traditional MRP systems by truly representing the dissembling process characteristics of the business and ensuring that planning decisions have a substantial positive effect on their margin.

What’sBest! new release offers many enhancements

Release 14 of What’sBest! includes a wide range of performance enhancements and new features, including:

  • Faster solutions on linear models with improved simplex solver
  • Improved integer solver with new features
  • Enhanced stochastic solver
  • Improved global solver
  • New scenario viewer

The new release includes additional enhancements, including improved model validity checking and more comprehensive error messages, new features to summarize location of the adjustable and constraint cells in the workbook to ease the understanding of the model, and added support for the standard deviation function STDEV.

Woolpert, FICO partner to help agencies meet cybersecurity order

Woolpert, a U.S. architecture, engineering and geospatial firm, has joined the FICO Enterprise Security Score partner program and will incorporate the score into its EC:Secure portfolio of products and services. This will allow Woolpert’s governmental and national security clients to accurately and effectively assess their cybersecurity risk.

“Under the recent Presidential Executive Order (E.O. 13800) on Strengthening the Cybersecurity of Federal Networks and Critical Infrastructure, all U.S. federal agencies need to take further steps to improve protection,” said Kim Hansen, Woolpert’s national security marketing manager. “We’re taking FICO’s advanced analytics to the federal government and enabling agencies to benchmark their performance, as well as that of their partners and vendors. It’s all part of keeping America safe.”

The FICO Enterprise Security Score provides an easy-to-understand metric that facilitates board-level risk assessment, third-party vendor management, and cyber breach insurance underwriting. Along with a score, the product provides current threat profile characteristics and granular insights into potential security issues to facilitate security posture remediation and continuous improvement processes. The score also helps organizations manage cyber-risks from vendors, business partners and other third parties.

In generating the Enterprise Security Score, FICO uses supervised machine learning algorithms to analyze thousands of components of an organization’s cybersecurity posture and behavior over time, and correlate these with observed data breach patterns. The result is an empirically derived view into cyber risk based on real mathematical equations, rather than arbitrary judgments or categorical assignments of points or grades. The score is based on data that is continuously collected at internet scale, allowing users to leverage the score and the underlying data infrastructure for continuous monitoring of risk – and ongoing remediation of issues – as threats, conditions and organizational behaviors change over time.

“The guidelines in the president’s executive order on cybersecurity line up perfectly with the FICO Enterprise Security Score,” said Doug Clare, vice president of cybersecurity solutions at FICO. “Woolpert is taking a leadership role in bringing these capabilities to government agencies.”

Optimization Direct creates new algorithm for massive MIP models

With bigger and more global data sets, customers are presenting increasingly large and complex models to optimize. With these massive models, established optimization technology generally fails in that it can either find no solution at all or solutions that take too long to find or are too poor to have any value. ODHeuristics, a new algorithm created by Optimization Direct, is designed to run on modern multiprocessor machines. Many cores (24+ ideal) are exploited by the ODHeuristics engine by breaking complex models and difficult MIPs into sub-models and solving them in parallel threads.

Optimization Direct has combined the new algorithm with CPLEX in the ODH-CPLEX Optimizer specifically to find solutions to massive MIP models of the big data era. The ODHeuristics engine is run under CPLEX in both deterministic or opportunistic modes; the combination of the two requires more memory and processor resources, but ODH accelerates CPLEX and helps CPLEX heuristics and finds good solutions to these massive data sets.

ODHeuristics is designed for scheduling problems but works for any MIP that has a reasonable number of integer feasible solutions. It has been deployed effectively on packing problems, supply chain and telecoms as well as scheduling applications. On large-scale MIPs it provides good solutions and optimality measures that are often beyond the reach of traditional optimization methods.