COIN-OR,Optimization Services (OS) User's Manual (2012)
The OS User's Manual provides information on downloading, installing, configuring and using the OS project.
Horand Gassmann, Jun Ma, Kipp Martin, Communication Protocols for Options and Results in a Distributed Optimization Environment, Mathematical Programming Computation (2015)
Much has been written about optimization instance formats. The MPS standard for linear mixed-integer programs is well known and has been around for many years. Other extensible formats are available for other optimization categories such as stochastic and nonlinear programming. However, the problem instance is not the only piece of information shared between the instance generator and the solver. Solver options and solver results must also be communicated.To our knowledge there is no commonly accepted format for representing either solver options or solver results. In this paper we propose a framework and theory for solver option and solver result representation in a modern distributed computing environment. A software implementation of the framework is available as an open-source COIN-OR project.
Horand Gassmann, Jun Ma, Kipp Martin, Instance Formats, book chapter in Encyclopedia of Operations Research and Management Science (2009)
In order to use an optimization solver, it is necessary to communicate an optimization instance to the solver. Additionally, solvers typically take options to specify tolerances, set algorithmic parameters, etc. Finally, the solver must communicate the result instance back to the user. In this article we review existing formats for optimization instances, solver option instances, and result instances and describe the research issues involved in designing these instance formats.
Joe Wirtley,Optimization Services at the Cincinnati Programmers' Guild (02/20/2008)
A very good article, short and clear, on the Optimization Services project.
MOSEK,C API Manual (2008)
MOSEK's capability with the standard OSiL xml format.
Robert Fourer, Jun Ma, Kipp Martin, Optimization Services: A Framework for Distributed Optimization, accepted at Operations Research (2009)
This paper describes the Optimization Services (OS) project. The OS project provides a framework consisting of standards for 1) representing optimization instances, results, and solver options, 2) communication between clients and solvers, and 3) the discovery and registration of optimization-related services in a distributed environment using Web Services. The ultimate goal of this project is to provide an environment where optimization system components, including modeling language environments, servers, registries, communication agents, interfaces, analyzers, solvers, and simulation engines, can be implemented as services under a unified framework so that customers can use these computational services much like utilities. We also describe a reference implementation that is a COIN-OR project.
Robert Fourer, Horand Gassmann, Jun Ma, Kipp Martin, An XML-based Schema for Stochastic Programs , final draft, accepted at the Annals of Operations Research (02, 2008)
This paper is in essense, adding stochastic program extension to OSiL (Optimization Services instance Language). It describes a proposed format to record instances of stochastic programs. It forms part of a larger XML-based schema that is designed to allow the expression of essentially any type of mathematical program within a unifying frame- work. A wide variety of different linear and nonlinear stochastic programs can be handled, and the paper describes in detail how this is done. Screen captures and sample problems illustrate the use of the schema.
This paper we present OSiL (Optimization Services instance Language), an XMLbased computer language for representing instances of large-scale optimization problems including linear programs, mixed-integer programs, quadratic programs, and very general nonlinear programs.
Robert Fourer, Leo Lopez, Kipp Martin, LPFML: A W3C XML Schema for Linear and Integer Programming, INFORMS Journal on Computing 17 (2005) 139-158.
This paper presents the LPFML Schema, a W3C Schema for representing linear programming problem instances in XML. LPFML is officially subsumed into the new version, OSiL (Optimization Services instance Language) by Robert Fourer, Jun Ma, Kipp Martin.
This doctoral thesis presents a general optimization system design introduced under our new concept of Optimization Services (OS) along with its Optimization Services Protocol (OSP). Optimization Services is intended to be a unified framework for the next generation distributed optimization systems, mainly optimization over the Internet. Thus Optimization Services can be regarded as the Operations Research Internet. The corresponding Optimization Services Protocol is intended to be a set of industrial standards.
Jun Ma, Optimization Services (OS) Summary, Thesis Summary, Industrial Engineering Management Sciences, Northwestern University (2005)
A 25-page short summary of the Optimization Services Thesis. It gives a general overview of the Optimization Services Framework and the corresponding Optimization Services Protocol.
R Fourer etc., NSF Project Summary, Next-Generation Servers for Optimization as an Internet Resource, Northwestern University and Argonne National Lab(2003)
The project proposal to National Science Foundation (NSF) that provides the necessary initial funding for the Optimization Services Research.
Kipp Martin , A Modeling System for Mixed Integer Linear Programming Using XML Technologies, Graduate School of Business, University of Chicago(2003)
The first conception of using XML technologies in mathematical modeling. This initiative is now fully subsumed into the Optimization Services modeling Language (OSmL) project.
Jun Ma, Optimization Services (OS) Proposal, Industrial Engineering Management Sciences, Northwestern University (2003)
The first conception of the Optimization Services. It lays out the original ideas and guidelines for designing and developing the Optimization Services framework.
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