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This article is cited in 3 scientific papers (total in 3 papers)
Collective bionic algorithm with biogeography based migration operator for binary optimization
Shakhnaz A. Akhmedova, Eugene S. Semenkin Department of System Analysis and Operation Research,
Reshetnev Siberian State Aerospace University,
Krasnoyarskiy Rabochiy, 31, Krasnoyarsk, 660037,
Russia
Abstract:
The meta-heuristic called Co-Operation of Biology Related Algorithms (COBRA) developed earlier for solving real-valued optimization problems has also been modified for solving optimization problems with binary variables (COBRA-b). The algorithm COBRA-b is based on a collective work of five nature-inspired algorithms' binary modifications such as Particle Swarm Optimization (PSO), the Wolf Pack Search Algorithm (WPS), the Firefly Algorithm (FFA), the Cuckoo Search Algorithm (CSA) and Bat Algorithm (BA). Its usefulness and workability were demonstrated on various benchmarks, and COBRA-b also outperformed its components. But solving problems sometimes required too many function evaluations, so the COBRA-b migration operator was modified by integrating biogeography principles for the speedup of the algorithm. Numerical experiments showed that the new modification exhibits high performance and outperforms COBRA-b and therefore its components.
Keywords:
biology inspired algorithms, biogeography, migration operator, optimization, binary variables.
Received: 26.11.2015 Received in revised form: 30.12.2015 Accepted: 25.01.2016
Citation:
Shakhnaz A. Akhmedova, Eugene S. Semenkin, “Collective bionic algorithm with biogeography based migration operator for binary optimization”, J. Sib. Fed. Univ. Math. Phys., 9:1 (2016), 3–10
Linking options:
https://www.mathnet.ru/eng/jsfu454 https://www.mathnet.ru/eng/jsfu/v9/i1/p3
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