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NEOS Server

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  • Comment: Because of the way that some of the references are formatted, they do not permit viewing the original paper. Please improve the formatting of the references so that a future reviewer can view the papers. Robert McClenon (talk) 01:08, 19 February 2016 (UTC)


The NEOS Server is an internet-based service for solving mathematical optimization problems. Since 2011, the NEOS Server has been hosted by the Wisconsin Insitute for Discovery at the University of Wisconsin in Madison. The NEOS Server provides access to more than 60 solvers -- commercial, free, and open source -- in more than a dozen optimization categories, including linear programming, integer programming, and nonlinear optimization. The NEOS Server was developed in 1996 by the Optimization Technology Center of Argonne National Laboratory and Northwestern University.

Most of the solvers accept optimization problems in AMPL and/or GAMS format and some accept LP format, MPS format or other solver-specific format. Users can submit jobs via a web interface, email, XML-RPC, Kestrel, or third-party submission tools. Solvers hosted by the University of Wisconsin in Madison run on distributed high-performance machines enabled by the HTCondor software; remote solvers run on machines at Argonne National Laboratory, Arizona State University, the University of Klagenfurt in Austria, and the University of Minho in Portugal.

Graphical depiction of the structure of the NEOS Server

Background

The NEOS (Network-Enabled Optimization System) project was launched in late 1994 by researchers at Argonne National Laboratory and Northwestern University. With the growth of the World Wide Web, the researchers were interested in exploring how to use the internet as a means of sharing existing, and growing new, optimization software resources.[1] The NEOS project included three components, the NEOS Server, the NEOS Guide, and NEOS tools. The NEOS Server is the name of the service for solving optimization problems remotely over the internet.[2][1][3] The NEOS Server went live in 1996, one of the first examples of Software_as_a_service.

Structure

The NEOS Server is an internet-based client-server application that provides access to a library of optimization solvers. NEOS uses the HTCondor software to schedule and manage the workload on a dedicated cluster of computers.[4]

Solvers on the NEOS Server solve optimization problems in many categories (listed below). The input formats to the NEOS Server include modeling languages, programming languages, and problem-specific input formats. Most of the linear programming, integer programming and nonlinear programming solvers accept input from AMPL and/or GAMS.

Users can submit jobs directly via a web submission interface, email, XML_RPC, Kestrel [5] or indirectly via third party submission tools (SolverStudio for Excel, OpenSolver, and Pyomo).

Types of Available Solvers

The NEOS Server provides access to solvers in the following optimization categories and more.

  • Bound Constrained Optimization: solvers for nonlinear optimization problems that are constrained only by bounds on the variables
  • Combinatorial Optimization: solvers for specific problems such as the Traveling Salesman Problem
  • Complementarity Problems: solvers for optimizing a function of two vector variables subject to constraint(s) including the requirement that the inner product of the two vectors must equal zero
  • Global Optimization:solvers for optimizing a general nonlinear function with the goal of finding the global minimum or maximum value
  • Linear Programming: solvers for optimizing a linear objective function subject to linear equality and linear inequality constraints
  • Mixed Integer Linear Programming: solvers for optimizing a linear program in which some or all of the variables are restricted to be integers
  • Mixed Integer Nonlinearly Constrained Optimization: solvers for nonlinear optimization problems in which at least some of the variables are restricted to discrete values
  • Nonlinearly Constrained Optimization: solvers for optimization problems in which some of the constraints and/or the objective function are nonlinear
  • Semidefinite Programming: solvers for optimizing a linear objective function over the intersection of the cone of positive semidefinite matrices with an affine space
  • Stochastic Linear Programming: solvers for optimizing problems in which some of the data incorporated into the objective function or constraints is uncertain
  • Second Order Cone Programming: solvers for convex optimization problems that include second-order cone constraints
  • Semi-Infinite Optimization: solvers for optimization problems with a finite number of variables and an infinite number of constraints or with an infinite number of variables and a finite number of constraints
  • Unconstrained Optimization: solvers for optimizing a function whose feasible region is not constrained

References

  1. ^ a b Czyzyk, Joseph; Owen, Jonathan H.; Wright, Stephen J. (1997). "Optimization on the Internet". OR/MS Today. 24 (5): 48-51.
  2. ^ Czyzyk, Joseph; Mesnier, Michael P.; Moré, Jorge J. (1998). "The NEOS Server". IEEE Journal on Computational Science and Engineering. 5 (3): 68 - 75.
  3. ^ Dolan, Elizabeth D.; Fourer, Robert; Moré, Jorge J.; Munson, Todd S. (2002). "Optimization on the NEOS Server" (PDF). SIAM News. 35 (6): 8-9.
  4. ^ Ferris, Michael C.; Mesnier, Michael P.; Moré, Jorge J. (2000). "NEOS and Condor: Solving Nonlinear Optimization Problems over the Internet". ACM Transactions on Mathematical Software. 26: 1–18.
  5. ^ Dolan, Elizabeth D.; Fourer, Robert; Goux, Jean-Pierre; Munson, Todd S.; Sarich, Jason (2008). "Kestrel: An Interface from Optimization Modeling Systems to the NEOS Server" (PDF). INFORMS Journal on Computing. 20 (4): 525 - 538.
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