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OSiL: An Instance Language for Optimization
"... Distributed computing technologies such as Web Services are growing rapidly in importance in today’s computing environment. In the area of mathematical optimization, it is becoming increasingly common to separate modeling languages from optimization solvers. In fact, the modeling language software, ..."
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Distributed computing technologies such as Web Services are growing rapidly in importance in today’s computing environment. In the area of mathematical optimization, it is becoming increasingly common to separate modeling languages from optimization solvers. In fact, the modeling language software, solver software, and data used to generate a model instance might reside on different machines using different operating systems. Such a distributed environment makes it critical to have an open standard for exchanging model instances. In this paper we present OSiL (Optimization Services instance Language), an XMLbased computer language for representing instances of largescale optimization problems including linear programs, mixedinteger programs, quadratic programs, and very general nonlinear programs. OSiL has two key features that make it much superior to current standard forms for optimization problem instances. First, it uses the objectoriented features of XML schemas to efficiently represent nonlinear expressions. Second, its XML schema maps directly into a corresponding inmemory representation of a problem instance. The inmemory representation provides a robust application program interface for general nonlinear programming, facilitates reading and writing postfix, prefix, and infix formats to and from the nonlinear expression tree, and makes the expression tree readily available for function and derivative evaluations. Key words: linear programming; nonlinear programming; modeling languages; information systems; web services; XML
Interfacing a Functional Logic Language with a Finite Domain Solver
 11th International Workshop on Functional and (Constraint) Logic Programming
, 2002
"... Abstract. In this paper, we present a straightforward way for interfacing the functional logic language T OY with a finite domain solver. Since T OY programs are compiled to Sicstus Prolog programs, we use the Sicstus ’ finite domain library to allow the expression of a finite domain problem in T OY ..."
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Abstract. In this paper, we present a straightforward way for interfacing the functional logic language T OY with a finite domain solver. Since T OY programs are compiled to Sicstus Prolog programs, we use the Sicstus ’ finite domain library to allow the expression of a finite domain problem in T OY. Finite domain T OY programs consist of functional logic T OY rules interfaced with constraint Sicstus clauses. This approach allows us to take advantage of the full functionality of Sicstus Prolog constraints.
The modeling system AIMMS for developing Mathematical Programming and Constraint Programming applications.
, 2013
"... Abstract. The Aimms package integrates externally supplied solution algorithms for mathematical programming and constraint programming with model development, application integration, and application deployment. In this context, some aspects of the technical realization of the extension of the AIMMS ..."
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Abstract. The Aimms package integrates externally supplied solution algorithms for mathematical programming and constraint programming with model development, application integration, and application deployment. In this context, some aspects of the technical realization of the extension of the AIMMS package with a CP interface will be discussed: – Element variables are an abstraction of integer variables permitting a natural extension of the subscripting capabilities in algebraic languages. – The Aimms Open Solver Interface to integrate solution algorithms is extended to communicate instruction arrays in order to communicate nonlinear expressions to the CP solvers. In addition, the topics of this workshop will be addressed. 1
Writing .nl Files
, 2005
"... AMPL r is a language and environment for describing mathematical programming problems and solving them. The AMPL processor interprets the AMPL language and invokes separate solvers to actually solve problems. It conveys problem information to solvers in ".nl" files. This paper describes the ..."
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AMPL r is a language and environment for describing mathematical programming problems and solving them. The AMPL processor interprets the AMPL language and invokes separate solvers to actually solve problems. It conveys problem information to solvers in ".nl" files. This paper describes the structure of a .nl file in enough detail to permit writing such a file without using the AMPL processor.
DESIGN PRINCIPLES AND NEW DEVELOPMENTS IN THE AMPL MODELING LANGUAGE
"... The design of the AMPL modeling language stresses naturalness of expressions, generality of iterating over sets, separation of model and data, ease of data manipulation, and automatic updating of derived values when fundamental values change. We show how such principles have guided the addition of d ..."
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The design of the AMPL modeling language stresses naturalness of expressions, generality of iterating over sets, separation of model and data, ease of data manipulation, and automatic updating of derived values when fundamental values change. We show how such principles have guided the addition of database access, complementarity modeling, and other language features.
The Aimms Interface to Constraint Programming
"... Abstract. We present an extension of the modeling system Aimms to handle constraint programming problems. Our goal is to provide a more accessible interface to CP technology than current systems offer. We first present basic CP modeling constructs that can be realized with minimum changes to the exi ..."
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Abstract. We present an extension of the modeling system Aimms to handle constraint programming problems. Our goal is to provide a more accessible interface to CP technology than current systems offer. We first present basic CP modeling constructs that can be realized with minimum changes to the existing syntax. We then discuss the handling of global constraints. Lastly, we present our extensions to modeling scheduling problems, based on the nowclassical representation as activities and resources. An important benefit of the Aimms interface to CP is the ease with which hybrid CP/OR solution methods can be developed. 1