The ICM in the DLM algorithm

Yousef Kilani, Abdullah Mohd. Zin

Research output: Contribution to journalArticle

Abstract

Local search methods for solving constraint satisfaction problems such as GSAT, WalkSAT and DLM starts the search for a solution from a random assignment. Local search then examines the neighbours of this assignment, using the penalty function to determine a better neighbour valuations to move to. It repeats this process until it finds a solution which satisfies all constraints. ICM [8] considers some of the constrai nts as hard constraints that are always satisfied. In this way, the constraints reduce the possible neighbours in each move and hence the overall search space. We choose t he hard constraints in such away that the space of valuations that satisfies these constraints is connected in order to guarantee that a local search can reach a solution from any valuation in this space. We show in this paper how incorporating learning in the isl and traps and restart improves the DLMI algorithm [8].

Original languageEnglish
Pages (from-to)457-463
Number of pages7
JournalWSEAS Transactions on Computers
Volume4
Issue number5
Publication statusPublished - May 2005

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Constraint satisfaction problems
Local search (optimization)

Keywords

  • SAT problems
  • The DLM local search algorithm

ASJC Scopus subject areas

  • Computer Science (miscellaneous)

Cite this

The ICM in the DLM algorithm. / Kilani, Yousef; Mohd. Zin, Abdullah.

In: WSEAS Transactions on Computers, Vol. 4, No. 5, 05.2005, p. 457-463.

Research output: Contribution to journalArticle

Kilani, Yousef ; Mohd. Zin, Abdullah. / The ICM in the DLM algorithm. In: WSEAS Transactions on Computers. 2005 ; Vol. 4, No. 5. pp. 457-463.
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