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2018
DOI: 10.1002/tee.22822
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Complete receptor editing operation based on quantum clonal selection algorithm for optimization problems

Abstract: Clonal selection mechanism, which is the theoretical foundation of clonal selection algorithm (CSA) and its variants, was proposed for explaining the essential features of adaptive immune responses: adequate diversity, discrimination of self and nonself, and sustaining immunologic memory. On the basis of the clonal selection theory, only the high‐affinity immune cells are chosen to proliferate. Those cells with low affinity must be efficiently eliminated. However, the ability of receptor editing to salvage low… Show more

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Cited by 5 publications
(3 citation statements)
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References 46 publications
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“…These two can well explain the behavior pattern of the algorithm in different stages and regions. When choosing an optimal solution, local exploration can speed up the convergence to the optimum, while diverse exploitation can prevent the algorithm from falling into a local optimum [79]. An appropriate alliance of aspects can ensure the implementation of a global optimal and accelerate the convergence rate.…”
Section: Exploitation and Explorationmentioning
confidence: 99%
“…These two can well explain the behavior pattern of the algorithm in different stages and regions. When choosing an optimal solution, local exploration can speed up the convergence to the optimum, while diverse exploitation can prevent the algorithm from falling into a local optimum [79]. An appropriate alliance of aspects can ensure the implementation of a global optimal and accelerate the convergence rate.…”
Section: Exploitation and Explorationmentioning
confidence: 99%
“…In future responses, these memory cells play a pre-eminent role against similar antigens (De Castro and Zuben, 2000;Coutinho, 1989). Several features of the adaptive immune system, such as diversity adequacy, discriminating between self and non-self and maintaining the memory of immunology, are explained by Yang et al (2019) using the clonal selection algorithm (CSA). The CSA provides proliferation and elimination of the cells that possess high affinitive.…”
Section: Clonal Selection Theorymentioning
confidence: 99%
“…In recent years, evolutionary computation has received great attention from researchers and practitioners due to its theoretical values for fundamentals of optimization and the flexibility of solving various problems arising from real-world applications. A great number of evolutionary computation algorithms have been proposed in the literature, including artificial immune systems [1]- [11] that imitate the adaptive immunological response mechanisms, differential evolution [12]- [14], gravitational search algorithms [15]- [20] inspired by the Newton's law of gravity and motion, ant colony optimization that models the rules of ants when they find foods [21], [22], imperialist competition algorithm [23]- [26] inspired from a social-politically motivated strategy, artificial bee colony algorithm [27], [28] inspired by the foraging behavior of the honey bee colony, etc. All these variants of evolutionary computation have achieved great success in solving many practical problems, such as artificial neural network learning [29]- [33], protein structure prediction [34]- [38], time series prediction [39], [40], dendritic neuron learning [41], [42], Internet of vehicles [43]- [45], and so on.…”
Section: Introductionmentioning
confidence: 99%