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ECLiPSe: A Powerful Constraint Logic Programming System for Problem Solving and Prototyping

ECLiPSe is a robust Constraint Logic Programming (CLP) system designed for a variety of programming tasks, particularly rapid prototyping and problem solving. It features a powerful runtime core, data-driven computation, backtracking, garbage collection, and interfaces for embedding within host environments like Java and C/C++. With a rich collection of libraries for constraint propagation, search and application support, and development tools such as Tkeclipse, ECLiPSe allows developers to create new solvers or leverage existing ones, ensuring flexible modeling and control for efficient problem resolution.

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ECLiPSe: A Powerful Constraint Logic Programming System for Problem Solving and Prototyping

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  1. Introduction

  2. ECLiPSe Components Constraint Logic Programming system, consisting of • A runtime core • Data-driven computation, backtracking, garbage collection • A collection of libraries • Constraint propagators, search support, application support, development support • A modelling and control language • Logic programming • A development environment • Tkeclipse • Interfaces for embedding into host environments • Java, Tcl/Tk, C/C++ • Interfaces to third-party solvers • Xpress-MP, Cplex, COIN-OR IC-Parc

  3. ECLiPSe Uses ECLiPSe is intended for • General programming tasks • especially rapid prototyping • Problem solving • using the CLP paradigm • using the available solver libraries • Development of new constraint solvers • employing ECLiPSe's lower-level language features • possibly based on the existing solvers IC-Parc

  4. Xi Cj How Does It Work - The C(L)P Paradigm Efficient Algorithms Model Heuristics Search IC-Parc

  5. Constraint (Logic) Programming Declarative Problem model Program = Logic + Control Control = Reasoning + Search Constraint propagation Clever algorithms Heuristics Problem specific knowledge IC-Parc

  6. Why use Logic Programming and Prolog? • Predicates over logical variables • Constraints over mathematical variables • (unlike ‘variable’ = storage location as in imperative languages!) • Program = Logic + Control • Solution = Model + Solver • Symbolic manipulation and metaprogramming • Program/data interchangeability is good for implementing solvers, programming search, preprocessing constraints, etc • Built-in backtracking • A general default mechanism for handling disjunctions • A convenient primitive for programming more complex search IC-Parc

  7. Constraint Program Template Algorithms deterministic efficiency :- lib(...). solve(Variables) :- setup_constraints(Variables), search(Variables). Model deterministic correctness Search nondeterministic choices & heuristics efficiency IC-Parc

  8. Logic Programming for Modelling X1{1..9} • Variables • can have attributes • e.g. domain, type • Constraints • = predicates, involving 1 or more variables • Model • = setup program _ #> _ _ #\= _ X2{3..9} alldifferent([ _, _, _ ]) [X1,X2,X3,X4]::1..9, X1 #> X2, alldifferent([X2,X3,X4]), X1 #\= X4. X4{1..7} X3{5..9} IC-Parc

  9. Logic Programming for Search • Binary choice ( X=0 ; X=1 ) • Enumerate ( X=1 ; X=2 ; X=3 ; X=4 ) X :: 1..4, indomain(X) • Split ( X #=< 5 ; X #> 5 ) • Heuristic choice ( X = Guess ; X #\= Guess ) IC-Parc

  10. Related Languages • Formal specification languages (e.g. B, Z, VDM) • More expressive power than ECLiPSe, but not executable • Mathematical modelling languages (e.g. OPL, AMPL) • Similar to ECLiPSe, but usually limited expressive power • (e.g. fixed set of constraints) and limited control • Search languages (Salsa, ToOls) • For expressing search strategies, special-purpose • Mainstream programming languages (e.g. C++ with ILOG) • Variables and constraints are “aliens” in the language • Specification mixed up with procedural control • Other CLP/high-level languages (e.g. CHIP, SICStus, Oz) • Most similar to ECLiPSe. Less support for hybrid problem solving. • Harder to define new constraints IC-Parc

  11. Components Covered in this Course • ECLiPSe Programming language • Constraint Solver Libraries • e.g. ic, eplex, ic_global, ic_sets, ic_symbolic, suspend • Search & Optimization Support Libraries • e.g. ic_search, branch_and_bound, repair • Constraint Building Support Libraries • e.g. propia, chr/ech • General Programming Support Libraries • e.g. lists, hash, … • Development Tools • e.g. tkeclipse, visualisation, coverage, profile, document IC-Parc

  12. Constraint Solver Libraries IC-Parc

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