Abstract
The knapsack problem is one of the well known NP-Hard optimization problems. Because of its appearance as a sub-problem in many real world problems, it attracts the attention of many researchers on swarm intelligence and evolutionary computation community. In this paper, a new binary artificial bee colony called NB-ABC is proposed to solve the 0-1 knapsack problem. Instead of the search operators of the original ABC, new binary search operators are designed for the different phases of the ABC algorithm, namely the employed, the onlooker and the scout bee phases. Moreover, a novel hybrid repair operator called (HRO) is proposed to repair and improve the infeasible solutions. To assess the performance of the proposed algorithm, NB-ABC is compared with two other existing algorithms, namely GB-ABC and BABC-DE, for solving the 0-1 knapsack problem. Based on a set of 15 0-1 high dimensional knapsack problems classified in three categories. the experimental results in view of many criteria show the efficiency and the robustness of the proposed NB-ABC.
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Acknowledgments
This work was partially supported by the National Natural Science Foundation of China (No. 61672215, U1613209).
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Nouioua, M., Li, Z., Jiang, S. (2018). New Binary Artificial Bee Colony for the 0-1 Knapsack Problem. In: Tan, Y., Shi, Y., Tang, Q. (eds) Advances in Swarm Intelligence. ICSI 2018. Lecture Notes in Computer Science(), vol 10941. Springer, Cham. https://doi.org/10.1007/978-3-319-93815-8_16
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DOI: https://doi.org/10.1007/978-3-319-93815-8_16
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