Open AccessAn improved salp optimization algorithm inspired by quantum computing
Author(s) -
Fanghao Tian,
Hong Wei,
Xu Li,
Meibo Lv,
Pei Wang
Publication year - 2020
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1570/1/012016
Subject(s) - quantum computer , quantum , quantum algorithm , qubit , algorithm , computer science , benchmark (surveying) , position (finance) , quantum state , quantum technology , quantum phase estimation algorithm , quantum simulator , physics , open quantum system , quantum mechanics , geodesy , finance , economics , geography
Salp Swarm Algorithm (SSA) is a novel optimization algorithm which is widely used in engineering problems. An improved SSA inspired by quantum computing is proposed in this paper. The principles of quantum computing, such as qubits and quantum states, are introduced into the original SSA in order to overcome the defect of trapping into local optimum easily. Instead of updating the salp position directly, the quantum angle related to the quantum state is updated to increase the diversity of states. Two multidimensional benchmark functions are used to verify the proposed improved SSA, the result shows that the introduction of quantum computing can successfully prevent the SSA from falling into the local optimum and increase the accuracy.