An introduction to genetic algorithms
An introduction to genetic algorithms
Dual-based heuristics for a hierarchical covering location problem
Computers and Operations Research
A Memetic Algorithm for Minimum-Cost Vertex-Biconnectivity Augmentation of Graphs
Journal of Heuristics
A detecting peak's number technique for multimodal function optimization
WSEAS Transactions on Information Science and Applications
Improving graph colouring algorithms and heuristics using a novel representation
EvoCOP'06 Proceedings of the 6th European conference on Evolutionary Computation in Combinatorial Optimization
The core concept for the multidimensional knapsack problem
EvoCOP'06 Proceedings of the 6th European conference on Evolutionary Computation in Combinatorial Optimization
A tool for comparing resource-constrained project scheduling problem algorithms
AIC'09 Proceedings of the 9th WSEAS international conference on Applied informatics and communications
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In this paper the two-level Hierarchical Covering Location Problem - HCLP is considered. A new genetic algorithm for that problem is developed, including specific binary encoding with the new crossover and mutation operators that keep the feasibility of individuals. Modification that resolves the problem of frozen bits in genetic code is proposed and tested. Version of fine-grained tournament [5] was used as well as the caching GA technique [12] in order to improve computational performance. Genetic algorithm was tested and its parameters were adjusted on number of test examples and it performed well and proved robust in all cases. Results were verified by CPLEX.