AIMMS

Last updated

AIMMS (acronym for Advanced Interactive Multidimensional Modeling System) is a prescriptive analytics software company with offices in the Netherlands, United States, and Singapore.

Contents

It has two main product offerings that provide modeling and optimization capabilities across a variety of industries. The AIMMS Prescriptive Analytics Platform allows advanced users to develop optimization-based applications and deploy them to business users. AIMMS SC Navigator, launched in 2017, is built on the AIMMS Prescriptive Analytics Platform and provides configurable Apps for supply chain teams. SC Navigator provides supply chain analytics to non-advanced users.

AIMMS
AIMMS logo.png
Designed by Johannes J. Bisschop
Marcel Roelofs
Developer AIMMS B.V. (formerly named Paragon Decision Technology B.V. [1] )
First appeared1993
Website AIMMS home page

History

AIMMS B.V. was founded in 1989 by mathematician Johannes Bisschop under the name of Paragon Decision Technology. His vision was to make optimization more approachable by building models rather than programming. In Bisschop's view, modeling was able to build the bridge between the people who had problems and the people helping them solve those problems.

AIMMS began as a software system designed for modeling and solving large-scale optimization and scheduling-type problems. [2] [3]

AIMMS is considered to be one of the five most important algebraic modeling languages. Bisschop was awarded with INFORMS Impact Prize for his work in this language. [4]

In 2003, AIMMS was acquired by a small private equity firm. This led to the creation of a partnership program, further technical investment and the evolution of the platform. In 2011, the company launched AIMMS PRO, a way to deploy applications to end-users who do not have a technical background. This was quickly followed by the ability to publish and customize applications using a browser so that decision support applications are available on any device.

The company grew and was in 2017 recognized as a top B2B technology in the Netherlands, [5] and was named one of the fastest-growing companies in the Netherlands for the second consecutive year. [6]

AIMMS SC Navigator Platform

Along with a growing interest in embedded advanced analytics for supply chain management, AIMMS developed the AIMMS SC Navigator Platform to allow for supply chain analytics. It was launched in October 2017 with three initial cloud-based Apps: Supply Chain Network Design, Sales & Operations Planning and Data Navigator. In 2018 they added Center of Gravity and Product Lifecycle.

AIMMS Prescriptive Analytics Platform

The AIMMS Prescriptive Analytics Platform consists of an algebraic modeling language, an integrated development environment for both editing models and creating a graphical user interface around these models, and a graphical end-user environment. [7] AIMMS is linked to multiple solvers through the AIMMS Open Solver Interface. [8] Supported solvers include CPLEX, MOSEK, FICO Xpress, CBC, Conopt, MINOS, IPOPT, SNOPT, KNITRO and CP Optimizer.

AIMMS features a mixture of declarative and imperative programming styles. Formulation of optimization models takes place through declarative language elements such as sets and indices, as well as scalar and multidimensional parameters, variables and constraints, which are common to all algebraic modeling languages, and allow for a concise description of most problems in the domain of mathematical optimization. Units of measurement are natively supported in the language, and compile- and runtime unit analysis may be employed to detect modeling errors.

Procedures and control flow statements are available in AIMMS for

To support the re-use of common modeling components, AIMMS allows modelers to organize their model in user model libraries.

AIMMS supports a wide range of mathematical optimization problem types:

Uncertainty can be taken into account in deterministic linear and mixed integer optimization models in AIMMS through the specification of additional attributes, such that stochastic or robust optimization techniques can be applied alongside the existing deterministic solution techniques.

Custom hybrid and decomposition algorithms can be constructed using the GMP system library which makes available at the modeling level many of the basic building blocks used internally by the higher level solution methods present in AIMMS, matrix modification methods, as well as specialized steps for customizing solution algorithms for specific problem types.

Optimization solutions created with AIMMS can be used either as a standalone desktop application or can be embedded as a software component in other applications.

Use in industry

AIMMS Prescriptive Analytics Platform is used in a wide range of industries including retail, consumer products, healthcare, oil and chemicals, steel production and agribusiness. [9] [10] [11]

GE Grid uses AIMMS as the modeling and optimization engine of its energy market clearing software. [12] Together with GE Grid, AIMMS was part of the analytics team of Midwest ISO that won the Franz Edelman Award for Achievement in Operations Research and the Management Sciences of 2011 for successfully applying operations research in the Midwest ISO energy market. [13] In 2012, TNT Express, an AIMMS customer won the Franz Edleman Award for modernizing its operations and reducing its carbon footprint. [14] The AIMMS platform was also used by the Dutch Delta team to develop and implement a new method for calculating the most efficient levels of flood protection for the Netherlands and won the Edelman prize in 2013. [15]

See also

Related Research Articles

<span class="mw-page-title-main">AMPL</span> Algebraic modeling language

AMPL is an algebraic modeling language to describe and solve high-complexity problems for large-scale mathematical computing . It was developed by Robert Fourer, David Gay, and Brian Kernighan at Bell Laboratories. AMPL supports dozens of solvers, both open source and commercial software, including CBC, CPLEX, FortMP, MOSEK, MINOS, IPOPT, SNOPT, KNITRO, and LGO. Problems are passed to solvers as nl files. AMPL is used by more than 100 corporate clients, and by government agencies and academic institutions.

IBM ILOG CPLEX Optimization Studio is an optimization software package.

The general algebraic modeling system (GAMS) is a high-level modeling system for mathematical optimization. GAMS is designed for modeling and solving linear, nonlinear, and mixed-integer optimization problems. The system is tailored for complex, large-scale modeling applications and allows the user to build large maintainable models that can be adapted to new situations. The system is available for use on various computer platforms. Models are portable from one platform to another.

SNOPT, for Sparse Nonlinear OPTimizer, is a software package for solving large-scale nonlinear optimization problems written by Philip Gill, Walter Murray and Michael Saunders. SNOPT is mainly written in Fortran, but interfaces to C, C++, Python and MATLAB are available.

<span class="mw-page-title-main">COIN-OR</span>

Computational Infrastructure for Operations Research (COIN-OR), is a project that aims to "create for mathematical software what the open literature is for mathematical theory." The open literature provides the operations research (OR) community with a peer-review process and an archive. Papers in operations research journals on mathematical theory often contain supporting numerical results from computational studies. The software implementations, models, and data used to produce the numerical results are typically not published. The status quo impeded researchers needing to reproduce computational results, make fair comparisons, and extend the state of the art.

The TOMLAB Optimization Environment is a modeling platform for solving applied optimization problems in MATLAB.

Algebraic modeling languages (AML) are high-level computer programming languages for describing and solving high complexity problems for large scale mathematical computation. One particular advantage of some algebraic modeling languages like AIMMS, AMPL, GAMS, Gekko, MathProg, Mosel, and OPL is the similarity of their syntax to the mathematical notation of optimization problems. This allows for a very concise and readable definition of problems in the domain of optimization, which is supported by certain language elements like sets, indices, algebraic expressions, powerful sparse index and data handling variables, constraints with arbitrary names. The algebraic formulation of a model does not contain any hints how to process it.

BARON is a computational system for solving non-convex optimization problems to global optimality. Purely continuous, purely integer, and mixed-integer nonlinear problems can be solved by the solver. Linear programming (LP), nonlinear programming (NLP), mixed integer programming (MIP), and mixed integer nonlinear programming (MINLP) are supported. In a comparison of different solvers, BARON solved the most benchmark problems and required the least amount of time per problem.

APOPT is a software package for solving large-scale optimization problems of any of these forms:

SAMPL, which stands for "Stochastic AMPL", is an algebraic modeling language resulting by expanding the well-known language AMPL with extended syntax and keywords. It is designed specifically for representing stochastic programming problems and, through recent extensions, problems with chance constraints, integrated chance constraints and robust optimization problems. It can generate the deterministic equivalent version of the instances, using all the solvers AMPL connects to, or generate an SMPS representation and use specialized decomposition based solvers, like FortSP.

OpenMDAO is an open-source high-performance computing platform for systems analysis and multidisciplinary optimization written in the Python programming language.

The FICO Xpress optimizer is a commercial optimization solver for linear programming (LP), mixed integer linear programming (MILP), convex quadratic programming (QP), convex quadratically constrained quadratic programming (QCQP), second-order cone programming (SOCP) and their mixed integer counterparts. Xpress includes a general purpose non-linear solver, Xpress NonLinear, including a successive linear programming algorithm, and Artelys Knitro.

LINDO is a software package for linear programming, integer programming, nonlinear programming, stochastic programming and global optimization.

Deterministic global optimization is a branch of mathematical optimization which focuses on finding the global solutions of an optimization problem whilst providing theoretical guarantees that the reported solution is indeed the global one, within some predefined tolerance. The term "deterministic global optimization" typically refers to complete or rigorous optimization methods. Rigorous methods converge to the global optimum in finite time. Deterministic global optimization methods are typically used when locating the global solution is a necessity, when it is extremely difficult to find a feasible solution, or simply when the user desires to locate the best possible solution to a problem.

Artelys Knitro is a commercial software package for solving large scale nonlinear mathematical optimization problems.

Algebraic modeling languages like AIMMS, AMPL, GAMS, MPL and others have been developed to facilitate the description of a problem in mathematical terms and to link the abstract formulation with data-management systems on the one hand and appropriate algorithms for solution on the other. Robust algorithms and modeling language interfaces have been developed for a large variety of mathematical programming problems such as linear programs (LPs), nonlinear programs (NPs), mixed integer programs (MIPs), mixed complementarity programs (MCPs) and others. Researchers are constantly updating the types of problems and algorithms that they wish to use to model in specific domain applications.

Gurobi Optimizer is a prescriptive analytics platform and a decision-making technology developed by Gurobi Optimization, LLC. The Gurobi Optimizer is a solver, since it uses mathematical optimization to calculate the answer to a problem.

References

  1. ↑ "We are moving forward, from now on you can call us AIMMS", "AIMMS". Archived from the original on 2013-10-29. Retrieved 2013-10-23.
  2. ↑ Kallrath, Joseph (2004). Modeling Languages in Mathematical Optimization. Kluwer Academic Publishing. ISBN   978-1-4020-7547-6.
  3. ↑ Roelofs, Marcel (2010). AIMMS Language Reference (PDF). lulu.com. ISBN   978-0-557-42456-6. Archived from the original (PDF) on June 7, 2015.
  4. ↑ "INFORMS Impact Prize - INFORMS". Archived from the original on 2013-10-22. Retrieved 2013-10-22.
  5. ↑ "The State of the Netherlands B2B Tech Scene in 2017". G2 Crowd. 2017-12-14. Retrieved 2018-04-12.
  6. ↑ "AIMMS :: AIMMS named one of the fastest growing companies in the Netherlands for the second consecutive year". AIMMS. Retrieved 2018-04-12.
  7. ↑ Roelofs, Marcel (2010). AIMMS User's Guide (PDF). lulu.com. ISBN   978-0-557-06360-4. Archived from the original (PDF) on 2015-06-07. Retrieved 2011-04-10.
  8. ↑ Paragon Decision Technology (2009). "AIMMS Open Solver Interface API".
  9. ↑ Lasschuit, Winston; Thijssen, Nort (15 June 2004). "Supporting supply chain planning and scheduling decisions in the oil and chemical industry" (PDF). Computers & Chemical Engineering. 28 (6–7, FOCAPO 2003 Special issue): 863–870. doi:10.1016/j.compchemeng.2003.09.026. Archived from the original (PDF) on 3 September 2011.
  10. ↑ "Integration and Optimisation of Crude Planning and Scheduling in the Hydrocarbon Supply Chain" (Press release). Shell Global Solutions. January 17, 2011.[ permanent dead link ]
  11. ↑ Medeiros Milanez, Eduardo (April 2010). "25 years of O.R. in Brazil". OR/MS Today. Archived from the original on April 12, 2010.
  12. ↑ Streiffert, D.; Philbrick, R.; Ott, A. (August 1, 2005). "A mixed integer programming solution for market clearing and reliability analysis" (PDF). Power Engineering Society General Meeting, 2005. IEEE. pp. 2724–2731 Vol. 3. doi:10.1109/PES.2005.1489108. Archived from the original (PDF) on August 13, 2011.
  13. ↑ "Midwest ISO Wins INFORMS Edelman Award" (Press release). INFORMS. April 11, 2011.
  14. ↑ INFORMS. "TNT Express Wins 2012 INFORMS Edelman Award, Super Bowl of Analytics, Operations Research". INFORMS. Archived from the original on 2019-02-21. Retrieved 2018-04-12.
  15. ↑ INFORMS. "Dutch Delta team earns Edelman". INFORMS. Retrieved 2018-04-12.


This page is based on this Wikipedia article
Text is available under the CC BY-SA 4.0 license; additional terms may apply.
Images, videos and audio are available under their respective licenses.