P.V. Hentenryck (1999). The OPL Optimization Programming Language. The MIT Press.  Home/Search   Document Not in Database   Summary   Related Articles   Check

....example is the CHIP system [DVS 88] The C library Ilog Solver [ILO97] demonstrated that the solving paradigm of constraint programming is programming language independent. The aim of the constraint programming languages Oz [Smo95, Moz99] and Claire [CL96b] and the modeling language OPL [Hen99] was to combine an expressive symbolic language for problem modeling with extensive support for problem solving. This paper guides the reader through the process of solving combinatorial problems using constraint programming. Section 2 gives an overview of the paradigm, explaining CP(FD) as a ....

....cooperate for problem solving. Sections 3, Section 4 and Section 5 describe propagation, branching and exploration algorithms in detail. This paper is intended as an overview of CP(FD) Stuckey and Marriott [MS98] give a thorough treatment of constraint programming in general, Van Hentenryck [Hen99] describes problem modeling and solving using CP(FD) and Wallace [Wal96] presents an overview of applications of constraint programming. 2 Problem Solving with Finite Domain Constraint Programming We focus on discrete search and optimization problems. Thus, decision variables in the considered ....

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Pascal Van Hentenryck. The OPL Optimization Programming Language. The MIT Press, Cambridge, MA, 1999.

....simplification before resorting to CSP solving. A number of uniform frameworks have been developed for expressing and simplifying common kinds of constraint problems; notable examples include the family of constraint logic programming (CLP) languages (Marriott Stuckey, 1998) the OPL language (Van Hentenryck, 1999), and Smith s algebraic theory of global search (Pepper Smith, 1996) For problems on discrete domains, these systems ultimately rely on brute force enumeration and testing of candidate solutions to a residual CSP, so an efficient CSP solver is an important system component. Integrating our ....

Van Hentenryck, P. (1999) The OPL Optimization Programming Language. MIT Press.

.... greedy algorithm and by trying many starting solutions, results are often disappointing. Practical local search methods must thus incorporate some device for getting away from local minimums. Indeed, local search methods are categorized according to the devices they use. Simulated annealing (van Laarhoven and Aarts 1987) allows occasional steps to solutions with worse objective values, according to a probability that is gradually reduced. Tabu search (Glover and Laguna 1997) also permits steps to inferior solutions, but promotes eventual progress by maintaining a list of recent solutions that may not be ....

P. van Hentenryck, The OPL Optimization Programming Language. MIT Press, Cambridge, MA. P.J.M. van Laarhoven and E.H.L. Aarts, 1987. Simulated Annealing: Theory and Applications. D. Reidel, Norwell, MA.

.... GNTHER, SRIVASTAVA, VIANU WALLACE 97] meta programming [PITRAT 93, pages 163 187] concurrent programming language design [HARIDI, VAN ROY, BRAND SCHULTE 98] design of algorithms that combine different paradigms [CASEAU LABURTHE 96a] operation research [GENDREAU 99] linear programming [VAN HENTENRYCK 99] and AI [DECHTER PEARL 87] As a matter of fact this is quite a good achievement for the constraint paradigm that has become popular so rapidly. However, this has also led to unexpected bad consequences: The first one is that there is no real common agreement on how constraints should be made ....

.... as a generalisation of a previous constraint [RGIN 94] RGIN 96] or as a completely new abstraction that was not related to any previously existing constraints [BELDICEANU CONTEJEAN 94] An attempt to be independent from any framework was to come out with an easy to use modelling language [VAN HENTENRYCK 99] that allows stating the constraints and the search procedure of a problem. However even within this approach all the constraints were considered as arbitrary predefined built in that are strongly dependent of the set of constraints that is provided by the underlying solver. If one looks to the ....

P. Van Hentenryck. The OPL Optimization Programming Language. The MIT Press, (1999).

....devices from constraint programming, but it does not address the issue of how solvers might cooperate to handle these extensions. 1. 4 Related Work 15 A recent algebraic modeling system, OPL, invokes both linear programming (ILOG Planner CPLEX) and constraint programming (ILOG Solver) solvers [138]. In OPL it is allowed to use both CP constraints and a linear relaxation, although the interface allows only limited forms of interaction. Links between CP and LP are one to one mappings of variables. Problemspecific search can be defined, overriding the default. We propose in Paper II that the ....

.... design [67, 81, 119] truss structure design [23] machine scheduling [74, 88] scheduling with resource constraints [114] highly combinatorial scheduling [81, 127] dynamic scheduling [50] production planning and transportation with piecewise linear functions [108, 121] warehouse location [20, 138], traveling salesman problem with time windows [54] hoist scheduling [126] maintenance scheduling of power plants [68] and problems with specially ordered sets [48] 1.4.7 Other Hybrid Approaches Integer and Linear Programming are not the only techniques which have been integrated with CP. Two ....

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Pascal Van Hentenryck. The OPL Optimization Programming Language. MIT Press, 1999. f15, 18, 26, 44, 52, 97, 99, 101, 103g

....protocols, transportation scheduling subject to initial and final location of the goods and the transportation resources, etc. Many of these problems can be expressed as constraint programs and then be solved using constraint solvers. Most of the available constraint solvers (clp(FD) 1] opl [13], etc) are equipped with constraint propagation algorithms based on consistency techniques such as node and arc consistency, plus a search algorithm such as forward checking, and a labeling heuristics, one of which is the default. To enhance the performance of a constraint program, a lot of ....

....research. 2 Subset Decision Problems We assume that CSP models are initially written in a very expressive, purely declarative, typed, first order set constraint logic programming language, such as our proposal in [3] here called esra, which is being designed to be higher level than even opl [13]. Using program synthesis techniques such as those in [11, 8, 2] we can automatically compile esra programs into lower level languages such as clp(FD) or opl. The purpose of this paper is not to discuss how this can be done, nor the syntax and semantics of esra. In the class of subset decision ....

P. Van Hentenryck. The opl Optimization Programming Language. The MIT Press, 1999. 6

.... network design [20, 27, 37] truss structure design [10] machine scheduling [21, 31] scheduling with resource constraints [34] highly combinatorial scheduling [27, 44] dynamic scheduling [15] production planning and transportation with piecewise linear functions [33, 38] warehouse location [9, 48], traveling salesman problem with time windows [16] hoist scheduling [43] and problems with specially ordered sets [14] A recent commercially available modeling system, OPL, invokes both linear programming (ILOG Planner CPLEX) and constraint programming (ILOG Solver) solvers [48] Despite these ....

.... location [9, 48] traveling salesman problem with time windows [16] hoist scheduling [43] and problems with specially ordered sets [14] A recent commercially available modeling system, OPL, invokes both linear programming (ILOG Planner CPLEX) and constraint programming (ILOG Solver) solvers [48]. Despite these developments, no generally accepted principle or scheme has evolved for the merger of optimization and constraint satisfaction. The purpose here is to propose such a scheme for unifying the solution methods of the two elds. We address elsewhere [27, 28, 30] the issue of a uni ed ....

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Pascal Van Hentenryck. The OPL Optimization Programming Language. MIT Press, 1999. 25

....solving. However, in some applications the need for a more formal and flexible formulation of constraint problems arises. This need is addressed in symbolic programming languages for constraint programming (Prolog based, Oz, claire) and in modeling languages for constraint programming such as OPL [Hen99] To address this need, we provide a generic interface to scripting languages such as Tcl and Perl. In addition to modeling, the use of scripting languages aids the development of and experimentation with the library and improves interoperability. Acknowledgements Gert Smolka collaborated on ....

Pascal Van Hentenryck. The OPL Optimization Programming Language. The MIT Press, Cambridge, MA, 1999.

....in modeling of combinatorial optimization problems. The element constraint is well known in the constraint programming world [24, 18] as a way of indexing discrete variables, but variable subscripts have now also been introduced in mathematical modeling languages such as AMPL [10, 22] and OPL [12]. While domain reduction ensuring arc or hyperarc consistency is relatively simple for indexing over discrete variables, the case of continuous variables is much less explored. The element constraint is written, element(y; v 1 ; v k ) z) 26) In the simplest case, y is a single ....

Pascal Van Hentenryck. The OPL Optimization Programming Language. MIT Press, 1999.

....(and speed up) constraint program development and to speed up the compiled programs. This philosophy is in line with the current trend of domain specific tools, such as the PLANWARE [2] system for planning problems, or the domain specific primitives of OPL (Optimisation Programming Language) [28] for scheduling and resource allocation problems. 5.1 Related Work This work is inspired by D.R. Smith s research on synthesising global search programs (in Refine) from first order logic specifications (also in Refine) with KIDS [23, 24] and its successor DESIGNWARE [25] Our work concentrates ....

....constraint languages, our input language is more expressive (by not being limited to sets of initially known size) and by design much faster. The OZ [26] language also allows sets of a priori unknown size [20] and is faster than ours, but it is less expressive and less declarative. The OPL [28] constraint language sets new standards in expressiveness, but is currently limited to membership constraints with ground sets (of known size) The DESIGNWARE system [25] maybe allows the formulation of constraints on possibly infinite sets and on sets whose elements are drawn from an infinite ....

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P. Van Hentenryck. The OPL Optimization Programming Language. The MIT Press, 1999.

....such general semi continuous piecewise functions is then a matter of nding the convex hull of a set of points. This is a well known problem in computational geometry and can be done eOEciently [4] A simpler syntax for continuous functions could of course be adopted, e.g. as in AMPL [16] and OPL [8], where the functions are assumed to be continuous and starting at the origin, and only the end point and slope of each segment are speci ed. 4 Algorithmic Extensions In CLP, good support for de ning problem speci c search strategies is essential. Strategies derive branching decisions from the ....

....unimodular probing, is used to derive constraint violations from a totally unimodular subset of linear inequalities solved as an LP. The violated constraints indicates possible branching choices. Similarly, the value extraction for shadowed variables, i.e. a variable present in both CP and LP [17,8], is also a special case of back propagation, allowing branching strategies based on the LP solution values. 4.2 Branching Strategies In a branching strategy there are two choices to make; what variable to branch and on, and what value to set it to. In IP it is very common to branch on the most ....

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Pascal Van Hentenryck. The OPL Optimization Programming Language. MIT Press, 1999.

....language (such as C or Prolog) and may therefore be less accessible and harder to use. Customized problem specific search procedures are common and often necessary. A recent effort made to overcome the gap between mathematical modeling languages and constraint programming systems is OPL [11], which allows mixing of discrete and continuous constraints and provides a high level way of describe problem specific search strategies. A second strength of mathematical programming is that the very structure of the modeling language anticipates the solution task. Although the human modeler may ....

Pascal Van Hentenryck. The OPL Optimization Programming Language. MIT Press, 1999.

....have weaker abstractions for algebraic and set manipulation. The work described in this paper originated as an attempt to unify modeling and constraint programming languages and their underlying implementation technologies. It led to the development of the optimization programming language OPL [13], its associated script language OPLSCRIPT [15] and its development environment OPL STUDIO. OPL is a modeling language sharing high level algebraic and set notations with traditional modeling languages. It also contains some novel functionalities to exploit sparsity in large scale applications, ....

P. Van Hentenryck. The OPL Optimization Programming Language. The MIT Press, Cambridge, Mass., 1999.

....the development of many modeling languages for mathematical programming (e.g. 4, 2] These languages significantly decrease the development time of optimization applications by providing high level algebraic and sets notations and data modeling facilities. Recent modeling languages such as OPL [8] further enhance these functionalities by supporting constraint programming notations and technologies and by letting modellers specify their search procedures for combinatorial optimization problems. Many practical applications however involve more than just solving a model, even when their ....

P. Van Hentenryck. The OPL Optimization Programming Language. The MIT Press, Cambridge, Mass., 1999.

....have weaker abstractions for algebraic and set manipulation. The work described in this paper originated as an attempt to unify modeling and constraint programming languages and their underlying implementation technologies. It led to the development of the optimization programming language OPL [13], its associated script language OPLSCRIPT [14] and its development environment OPL STUDIO. OPL is a modeling language sharing high level algebraic and set notations with traditional modeling languages. It also contains some novel functionalities to exploit sparsity in large scale applications, ....

P. Van Hentenryck. The OPL Optimization Programming Language. The MIT Press, Cambridge, Mass., 1999.

....have weaker abstractions for algebraic and set manipulation. The work described in this paper originated as an attempt to unify modeling and constraint programming languages and their underlying implementation technologies. It led to the development of the optimization programming language OPL [10], its associated script language OPLSCRIPT [9] and its development environment OPL STUDIO. OPL is a modeling language sharing high level algebraic and set notations with traditional modeling languages. It also contains some novel functionalities to exploit sparsity in large scale applications, ....

P. Van Hentenryck. The OPL Optimization Programming Language. The MIT Press, Cambridge, Mass., 1999.

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P.V. Hentenryck (1999). The OPL Optimization Programming Language. The MIT Press.

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