Monadic constraint programming

A constraint programming system combines two essential components: a constraint solver and a search engine. The constraint solver reasons about satisfiability of conjunctions of constraints, and the search engine controls the search for solutions by iteratively exploring a disjunctive search tree defined by the constraint program. In this paper we give a monadic definition of constraint programming in which the solver is defined as a monad threaded through the monadic search tree. We are then able to define search and search strategies as first-class objects that can themselves be built or extended by composable search transformers. Search transformers give a powerful and unifying approach to viewing search in constraint programming, and the resulting constraint programming system is first class and extremely flexible

Memoizing a monadic mixin DSL

Modular extensibility is a highly desirable property of a domain-specific language (DSL): the ability to add new features without affecting the implementation of existing features. Functional mixins (also known as open recursion) are very suitable for this purpose. We study the use of mixins in Haskell for a modular DSL for search heuristics used in systematic solvers for combinatorial problems, that generate optimized C++ code from a high-level specification. We show how to apply memoization techniques to tackle performance issues and code explosion due to the high recursion inherent to the semantics of combinatorial search. As such heuristics are conventionally implemented as highly entangled imperative algorithms, our Haskell mixins are monadic. Memoization of monadic components causes further complications for us to deal with

Improving the Search Capabilities of a CFLP(FD) System

The CFLP system TOY(FD) is implemented in SICStus Prolog, and supports FD constraints by interfacing the CP(FD) solvers of Gecode and ILOG Solver. In this paper TOY(FD) is extended with new search primitives, in a setting easily adaptable to other Prolog CLP or CFLP systems. The primitives are described from a solver-independent point of view, pointing out some novel concepts not directly available in the Gecode and ILOG Solver libraries, as well as how to specify some search criteria at TOY(FD) level and how easily these strategies can be combined to set different search scenarios. The implementation of the primitives is described, presenting an abstract view of the requirements and how they are targeted to the Gecode and ILOG libraries. Finally, some benchmarks show that the new search strategies improve the solving performance of TOY(FD)

Haiku - a Scala combinator toolkit for semi-automated composition of metaheuristics

There is an emerging trend towards the automated design of metaheuristics at the software component level. In principle, metaheuristics have a relatively clean decomposition, where well-known frameworks such as ILS and EA are parametrised by variant components for acceptance, perturbation etc. Automated generation of these frameworks is not so simple in practice, since the coupling between components may be implementation specific. Compositionality is the ability to freely express a space of designs ‘bottom up’ in terms of elementary components: previous work in this area has used combinators, a modular and functional approach to componentisation arising from foundational Computer Science. In this article, we describeHaiku, a combinator tool-kit written in the Scala language, which builds upon previous work to further automate the process by automatically composing the external dependencies of components. We provide examples of use and give a case study in which a programatically-generated heuristic is applied to the Travelling Salesman Problem within an Evolutionary Strategies framework

Generic programming with C++ concepts and Haskell type classes—a comparison

Earlier studies have introduced a list of high-level evaluation criteria to assess how well a language supports generic programming. Languages that meet all criteria include Haskell, because of its type classes, and C++ with the concept feature. We refine these criteria into a taxonomy that captures commonalities and differences between type classes in Haskell and concepts in C++, and discuss which differences are incidental and which ones are due to other language features. The taxonomy allows for an improved understanding of language support for generic programming, and the comparison is useful for the ongoing discussions among language designers and users of both languages

Structured Traversal of Search Trees in Constraint-logic Object-oriented Programming

In this paper, we propose an explicit, non-strict representation of search trees in constraint-logic object-oriented programming. Our search tree representation includes both the non-deterministic and deterministic behaviour during execution of an application. Introducing such a representation facilitates the use of various search strategies. In order to demonstrate the applicability of our approach, we incorporate explicit search trees into the virtual machine of the constraint-logic object-oriented programming language Muli. We then exemplarily implement three search algorithms that traverse the search tree on-demand: depth-first search, breadth-first search, and iterative deepening depth-first search. In particular, the last two strategies allow for a complete search, which is novel in constraint-logic object-oriented programming and highlights our main contribution. Finally, we compare the implemented strategies using several benchmarks.Comment: Part of DECLARE 19 proceeding