Frontline Systems Analytic Solver Platform with Simulation/Risk Analysis, Optimization Enhancements
Frontline Systems, Version 2016-R2 of its Solvers for Excel, release includes wide-ranging enhancements in Monte Carlo simulation and optimization technology, plus the ability to convert Excel analytic models into free-standing web and mobile applications. “We’re fulfilling our promise of ‘no-compromise analytic power’ for Excel users,” said Daniel Fylstra, Frontline’s President and CEO. “Business analysts can build models with point-and-click ease of use, while taking advantage of the most advanced analytic algorithms and methods.” In just four months since release of Analytic Solver Platform V2016, Frontline has added functionality comparable to a years’ worth of many competitors’ offerings.
The new release features significant enhancements to Frontline’s popular Evolutionary Solver, focusing on models with integer variables – often yielding dramatically better solutions in a given amount of time, compared to Frontline’s previous releases and competitive products. These enhancements build on the SQP-GS (Sequential Quadratic Programming with Gradient Sampling) for local search, and Feasibility Pump algorithms introduced in Frontline Solvers V2016.
The new release also includes performance enhancements for multi-dimensional optimization and simul¬ation models that use the Dimensional Modeling features of Analytic Solver Platform, first introduced in Frontline Solvers V2014, in the frequently-occurring case where multi-dimensional data is ‘sparse’. Memory use and time computing multi-dimensional formulas is dramatically reduced for these models.
In Monte Carlo simulation, the V2016-R2 release supports correlation of uncertain variables with dissimilar distributions, using Gaussian, Student and Archimedean (Clayton, Frank and Gumbel) copulas – complementing existing support for rank-order correlation. Copulas for correlation are popular in quantitative finance models. All the methods are available are available via a simple point-and-click correlation dialog that allows the user to preview scatter plots showing how samples from uncertain variables will be generated and correlated.
The new release also supports ‘compound distributions’ – often used in actuarial and insurance models – where samples are generated and aggregated from multiple instances of a probability distribution – called the ‘severity’ distribution. The number of instances can be a constant or a sample from another, discrete probability distribution, called the ‘frequency’ distribution. Nearly all of Analytic Solver’s 50+ analytic distributions can be used, and for many common distributions, the software uses analytic methods in lieu of repeated sampling for speed.
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