Solving constraint satisfaction problems using firefly algorithms

Abstract

Constraints Satisfaction Problems (CSPs) are known to be hard to solve and require a backtrack search algorithm with exponential time cost. Metaheuristics have recently gained much reputation for solving complex problems and can be employed as an alternative to tackle CSPs even if, in theory, they do not guarantee a complete solution to the problem. This paper proposes a new Discrete Firefly Algorithm (DFA) and investigates its applicability for dealing with CSPs. To assess the performance of the proposed DFA, experiments have been conducted on CSP instances, randomly generated based on the Model RB. The results of the experiments clearly demonstrate the significant performance of the proposed method in dealing with CSPs. For all the instances tested, DFA is successful to find a complete solution that satisfies all constraints in a reasonable amount of time.