
Effects of Dynamic Variable - Value Ordering Heuristics on the Search Space of Sudoku Modeled as a Constraint Satisfaction Problem
Author(s) -
James L. Cox,
Stephen Lucci,
Tayfun Pay
Publication year - 2019
Publication title -
inteligencia artificial
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.149
H-Index - 12
eISSN - 1988-3064
pISSN - 1137-3601
DOI - 10.4114/intartif.vol22iss63pp1-15
Subject(s) - heuristics , heuristic , variable (mathematics) , constraint satisfaction problem , lexicographical order , mathematical optimization , computer science , constraint (computer aided design) , value (mathematics) , constraint satisfaction , algorithm , mathematics , artificial intelligence , machine learning , mathematical analysis , geometry , combinatorics , probabilistic logic
We carry out a detailed analysis of the effects of different dynamic variable and value ordering heuristics on the search space of Sudoku when the encoding method and the filtering algorithm are fixed. Our study starts by examining lexicographical variable and value ordering and evaluates different combinations of dynamic variable and value ordering heuristics. We eventually build up to a dynamic variable ordering heuristic that has two rounds of tie-breakers, where the second tie-breaker is a dynamic value ordering heuristic. We show that our method that uses this interlinked heuristic outperforms the previously studied ones with the same experimental setup. Overall, we conclude that constructing insightful dynamic variable ordering heuristics that also utilize a dynamic value ordering heuristic in their decision making process could drastically improve the search effort for some constraint satisfaction problems.