A multipopulation cultural algorithm based on genetic algorithm for the MKP
Proceedings of the 11th Annual conference on Genetic and evolutionary computation
Solving weighted constraint satisfaction problems with memetic/exact hybrid algorithms
Journal of Artificial Intelligence Research
A probabilistic beam search approach to the shortest common supersequence problem
EvoCOP'07 Proceedings of the 7th European conference on Evolutionary computation in combinatorial optimization
Efficient stochastic local search algorithm for solving the shortest common supersequence problem
Proceedings of the 12th annual conference on Genetic and evolutionary computation
A particle swarm optimization based memetic algorithm for dynamic optimization problems
Natural Computing: an international journal
Hybrid metaheuristics in combinatorial optimization: A survey
Applied Soft Computing
Evolutionary-based iterative local search algorithm for the shortest common supersequence problem
Proceedings of the 13th annual conference on Genetic and evolutionary computation
A cooperative tree-based hybrid GA-B&B approach for solving challenging permutation-based problems.
Proceedings of the 13th annual conference on Genetic and evolutionary computation
A multi-level memetic/exact hybrid algorithm for the still life problem
PPSN'06 Proceedings of the 9th international conference on Parallel Problem Solving from Nature
An enhanced beam search algorithm for the Shortest Common Supersequence Problem
Engineering Applications of Artificial Intelligence
A memetic particle swarm optimization algorithm for multimodal optimization problems
Information Sciences: an International Journal
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Branch-and-bound (BnB) and memetic algorithms represent two very different approaches for tackling combinatorial optimization problems. However, these approaches are compatible. In this correspondence, a hybrid model that combines these two techniques is considered. To be precise, it is based on the interleaved execution of both approaches. Since the requirements of time and memory in BnB techniques are generally conflicting, a truncated exact search, namely, beam search, has opted to be carried out. Therefore, the resulting hybrid algorithm has a heuristic nature. The multidimensional 0-1 knapsack problem and the shortest common supersequence problem have been chosen as benchmarks. As will be shown, the hybrid algorithm can produce better results in both problems at the same computational cost, especially for large problem instances