A Binary Butterfly Optimization Algorithm for the Multidimensional Knapsack Problem
The Multidimensional knapsack problem (MKP) is a well-known optimization problem with which many real-world engineering problems can be modeled. Due to its NP-hard nature, exact methods of solving the MKP are limited to small-scale problems. Therefore, in the past decade, various meta-heuristics hav...
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| Published in: | 2020 6th Iranian Conference on Signal Processing and Intelligent Systems (ICSPIS) pp. 1 - 5 |
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| Main Authors: | , |
| Format: | Conference Proceeding |
| Language: | English |
| Published: |
IEEE
23.12.2020
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| Subjects: | |
| Online Access: | Get full text |
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| Summary: | The Multidimensional knapsack problem (MKP) is a well-known optimization problem with which many real-world engineering problems can be modeled. Due to its NP-hard nature, exact methods of solving the MKP are limited to small-scale problems. Therefore, in the past decade, various meta-heuristics have been developed to solve the MKP in a reasonable time. Butterfly optimization algorithm (BOA) is a recently developed meta-heuristic that has shown good convergence ability as well as avoiding local optima stagnation. In this paper, a binary version of BOA (BBOA) is proposed to solve the 0-1 MKP. BOA is originally designed for a continuous search space therefore in this paper, we propose six binary versions of BOA using three S-shaped and three V-shaped transfer functions and determine the most effective version through experiments. The proposed BBOA also includes an initial population generator and a repair operator based on the pseudo-utility. To evaluate the proposed method, 11 medium-scale and large-scale benchmark problems are employed and BBOA is compared to other competitive algorithms. |
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| DOI: | 10.1109/ICSPIS51611.2020.9349589 |