Results 1  10
of
86
Constraint Programming in OPL
 In Proceedings of the International Conference on the Principles and Practice of Declarative Programming (PPDP'99
, 1999
"... OPL is a modeling language for mathematical programming and combinatorial optimization problems. It is the first modeling language to combine highlevel algebraic and set notations from modeling languages with a rich constraint language and the ability to specify search procedures and strategies tha ..."
Abstract

Cited by 35 (5 self)
 Add to MetaCart
(Show Context)
OPL is a modeling language for mathematical programming and combinatorial optimization problems. It is the first modeling language to combine highlevel algebraic and set notations from modeling languages with a rich constraint language and the ability to specify search procedures and strategies that is the essence of constraint programming. In addition, OPL models can be controlled and composed using OPLSCRIPT, a script language that simplifies the development of applications that solve sequences of models, several instances of the same model, or a combination of both as in columngeneration applications. This paper illustrates some of the functionalities of OPL for constraint programming using frequency allocation, sportscheduling, and jobshop scheduling applications. It also illustrates how OPL models can be composed using OPLSCRIPT on a simple configuration example.
Constraint and Integer Programming in OPL
 INFORMS Journal on Computing
, 2002
"... In recent years, it has been increasingly recognized that constraint and integer programming have orthogonal and complementary strengths in stating and solving combinatorial optimization applications. In addition, their integration has become an active research topic. The optimization programming la ..."
Abstract

Cited by 26 (7 self)
 Add to MetaCart
(Show Context)
In recent years, it has been increasingly recognized that constraint and integer programming have orthogonal and complementary strengths in stating and solving combinatorial optimization applications. In addition, their integration has become an active research topic. The optimization programming language opl was a first attempt at integrating these technologies both at the language and at the solver levels. In particular, opl is a modeling language integrating the rich language of constraint programming and the ability to specify search procedures at a high level of abstraction. Its implementation includes both constraint and mathematical programming solvers, as well as some cooperation schemes to make them collaborate on a given problem. The purpose of this paper is to illustrate, using opl, the constraintprogramming approach to combinatorial optimization and the complementary strengths of constraint and integer programming. (Artificial Intelligence; Computer Science; Integer Programming) 1.
AMPL: A mathematical programming language
, 1989
"... Practical largescale mathematical programming involves more than just the application of an algorithm to minimize or maximize an objective function. Before any optimizing routine can be invoked, considerable effort must be expended to formulate the underlying model and to generate the requisite com ..."
Abstract

Cited by 20 (1 self)
 Add to MetaCart
(Show Context)
Practical largescale mathematical programming involves more than just the application of an algorithm to minimize or maximize an objective function. Before any optimizing routine can be invoked, considerable effort must be expended to formulate the underlying model and to generate the requisite computational data structures. AMPL is a new language designed to make these steps easier and less errorprone. AMPL closely resembles the symbolic algebraic notation that many modelers use to describe mathematical programs, yet it is regular and formal enough to be processed by a computer system; it is particularly notable for the generality of its syntax and for the variety of its indexing operations. We have implemented a translator that takes as input a linear AMPL model and associated data, and produces output suitable for standard linear programming optimizers. Both the language and the translator admit straightforward extensions to more general mathematical programs that incorporate nonlinear expressions or discrete variables
Search and Strategies in OPL
, 2000
"... OPL is a modeling language for mathematical programming and combinatorial optimization. It is the first language to combine highlevel algebraic and set notations from mathematical modeling languages with a rich constraint language and the ability to specify search procedures and strategies that are ..."
Abstract

Cited by 20 (2 self)
 Add to MetaCart
OPL is a modeling language for mathematical programming and combinatorial optimization. It is the first language to combine highlevel algebraic and set notations from mathematical modeling languages with a rich constraint language and the ability to specify search procedures and strategies that are the essence of constraint programming. This paper describes the facilities available in OPL to specify search procedures. It describes the abstractions of OPL to specify both the search tree (search) and how to explore it (strategies). The paper also illustrates how to use these highlevel constructs to implement traditional search procedures in constraint programming and scheduling.
TOMLAB  An Environment for Solving Optimization Problems in MATLAB
 PROCEEDINGS FOR THE NORDIC MATLAB CONFERENCE '97
, 1997
"... TOMLAB is a general purpose, open and integrated MATLAB environment for solving optimization problems on UNIX and PC systems. TOMLAB has meny systems and driver routines for the most common optimization problems and more than 50 algorithms implemented in the toolbox NLPLIB and the toolbox OPERA. N ..."
Abstract

Cited by 16 (12 self)
 Add to MetaCart
(Show Context)
TOMLAB is a general purpose, open and integrated MATLAB environment for solving optimization problems on UNIX and PC systems. TOMLAB has meny systems and driver routines for the most common optimization problems and more than 50 algorithms implemented in the toolbox NLPLIB and the toolbox OPERA. NLPLIB TB 1.0 is a MATLAB toolbox for nonlinear programming and parameter estimation and OPERA TB 1.0 is a MATLAB toolbox for operational research, with emphasis on linear and discrete optimization. Of special interest in NLPLIB TB 1.0 are the algorithms for general and separable nonlinear least squares parameter estimation. TOMLAB is using MEXfile interfaces to call solvers written in C/C++ and FORTRAN. Currently MEXfile interfaces have been developed for the commercial solvers MINOS, NPSOL, NPOPT, NLSSOL, LPOPT, QPOPT and LSSOL. From TOMLAB it is also possible to call routines in the MathWorks Optimization Toolbox. Interfaces are available for the model language AMPL and the CUTE (Cons...
TOMLAB  A General Purpose, Open MATLAB Environment for Research and Teaching in Optimization
, 1998
"... TOMLAB is a general purpose, open and integrated MATLAB environment for research and teaching in optimization on UNIX and PC systems. The motivation for TOMLAB is to simplify research on practical optimization problems, giving easy access to all types of solvers; at the same time having full acce ..."
Abstract

Cited by 14 (13 self)
 Add to MetaCart
TOMLAB is a general purpose, open and integrated MATLAB environment for research and teaching in optimization on UNIX and PC systems. The motivation for TOMLAB is to simplify research on practical optimization problems, giving easy access to all types of solvers; at the same time having full access to the power of MATLAB. By using a simple, but general input format, combined with the ability in MATLAB to evaluate string expressions, it is possible to run internal TOMLAB solvers, MATLAB Optimization Toolbox and commercial solvers written in FORTRAN or C/C++ using MEXfile interfaces. Currently MEXfile interfaces have been developed for MINOS, NPSOL, NPOPT, NLSSOL, LPOPT, QPOPT and LSSOL. TOMLAB may either be used totally parameter driven or menu driven. The basic principles will be discussed. The menu system makes it suitable for teaching. Many standard test problems are included. More test problems are easily added. There are many example and demonstration files. Iterati...
Expressing Special Structures in an Algebraic Modeling Language for Mathematical Programming
, 1995
"... A knowledge of the presence of certain special structures can be advantageous in both the formulation and solution of linear programming problems. Thus it is desirable that linear programming software o#er the option of specifying such structures explicitly. As a step in this direction, we describe ..."
Abstract

Cited by 14 (4 self)
 Add to MetaCart
A knowledge of the presence of certain special structures can be advantageous in both the formulation and solution of linear programming problems. Thus it is desirable that linear programming software o#er the option of specifying such structures explicitly. As a step in this direction, we describe extensions to an algebraic modeling language that encompass piecewiselinear, network and related structures. Our emphasis is on the modeling considerations that motivate these extensions, and on the design issues that arise in integrating these extensions with the generalpurpose features of the language. We observe that our extensions sometimes make models faster to translate as well as to solve, and that they permit a "columnwise" formulation of the constraints as an alternative to the "rowwise" formulation most often associated with algebraic languages.
Computerbased modeling environments
, 1989
"... This paper gives the author's views on the kind of computerbased modeling environment needed to properly support management science/operations research work, and on the design challenges that need to be met in order to bring such modeling environments into being. It is a written version of th ..."
Abstract

Cited by 14 (4 self)
 Add to MetaCart
This paper gives the author's views on the kind of computerbased modeling environment needed to properly support management science/operations research work, and on the design challenges that need to be met in order to bring such modeling environments into being. It is a written version of the main ideas of two addresses: a plenary at IFORS 87 in Buenos Aires (August, 1987), and the keynote at the
Localizer++: An Open Library for Local Search
, 2001
"... Local search is one of the fundamental approaches to tackle large combinatorial optimization problems. Yet relatively little support is available to facilitate the design and implementation of local search algorithms. This paper introduces Localizer , an extensible objectoriented library for local ..."
Abstract

Cited by 13 (2 self)
 Add to MetaCart
(Show Context)
Local search is one of the fundamental approaches to tackle large combinatorial optimization problems. Yet relatively little support is available to facilitate the design and implementation of local search algorithms. This paper introduces Localizer , an extensible objectoriented library for local search. Localizer supports both declarative abstractions to describe the neighborhood and highlevel search constructs to specify local moves and metaheuristics. It also supports a variety of features typically found only in modeling languages and its extensibility allows for an easy integration of new, userdefined, abstractions. Of particular interest is the conciseness and readability of Localizer statements and the efficiency of the Localizer implementation.
The TOMLAB Optimization Environment in Matlab
, 1999
"... TOMLAB is a general purpose, open and integrated Matlab development environment for research and teaching in optimization on Unix and PC systems. One motivation for TOMLAB is to simplify research on practical optimization problems, giving easy access to all types of solvers; at the same time having ..."
Abstract

Cited by 12 (0 self)
 Add to MetaCart
(Show Context)
TOMLAB is a general purpose, open and integrated Matlab development environment for research and teaching in optimization on Unix and PC systems. One motivation for TOMLAB is to simplify research on practical optimization problems, giving easy access to all types of solvers; at the same time having full access to the power of Matlab. The design principle is: define your problem once, optimize using any suitable solver. In this paper we discuss the design and contents of TOMLAB, as well as some applications where TOMLAB has been successfully applied. TOMLAB is based on NLPLIB TB, a Matlab toolbox for nonlinear programming and parameter estimation, and OPERA TB 1.0, a Matlab toolbox for linear and discrete optimization. More than 65 different algorithms and graphical utilities are implemented. It is possible to call solvers in the Matlab Optimization Toolbox and generalpurpose solvers implemented in Fortran or C using a MEXfile interface. Currently, MEXfile interfaces have been developed for