Intelligent backtracking on constraint satisfaction problems: experimental and theoretical results
Intelligent backtracking on constraint satisfaction problems: experimental and theoretical results
A Glimpse of Constraint Satisfaction
Artificial Intelligence Review
Artificial Intelligence: A Modern Approach
Artificial Intelligence: A Modern Approach
Performance measurement and analysis of certain search algorithms.
Performance measurement and analysis of certain search algorithms.
Algorithms and heuristics for constraint satisfaction problems
Algorithms and heuristics for constraint satisfaction problems
Constraint satisfaction problems solved by semidefinite relaxations
WSEAS Transactions on Computers
Combinatorial optimization: mutual relations among graph algorithms
WSEAS Transactions on Mathematics
Benchmarking in digital circuit design automation
WSEAS Transactions on Circuits and Systems
Design and implementation of soil spatial variation analysis system
WSEAS Transactions on Information Science and Applications
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A constraint satisfaction problem (CSP) involves assigning possible values to a set of variables without defying any constraints. There are various techniques available to solve or give partial solution to CSP. This paper presents a modification of branch and bound algorithm, which is used to solve a constraint satisfaction problem in map colouring problem. There are two constraints involved which are only three colours are allowed to be used and adjacent regions in the map must not be of the same colour. The modified branch and bound algorithm uses back jumping when it encounters a dead-end in the search. Static variable ordering was also applied to aid the searching process. The modified branch and bound algorithm shows a better result in terms of the number of nodes instantiated and the reduced number of backtracking at dead ends. The result illustrated that the modified branch and bound algorithm with the use of variable ordering technique is better if compared to backjumping. Thus, it is concluded that the modified branch and bound algorithm would improve constraint satisfaction problem.