Dynamic diversity control in genetic algorithm for mining unsearched solution space in TSP problems

Chang, Pei‐Chann; Huang, Wei-Hsiu; Ting, Ching‐Jung

doi:10.1016/j.eswa.2009.07.066

Cited by 67 publications

(28 citation statements)

References 21 publications

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“…, the diversity of the proposed algorithm is lower than those of the others. The usual view is that a higher diversity is beneficial for avoiding premature convergence and escaping from local optima of an algorithm . However, based on our experimental results, diversity is not the only key to the performance of the algorithm.…”

Section: Simulation and Discussionmentioning

confidence: 89%

Complete receptor editing operation based on quantum clonal selection algorithm for optimization problems

Dai

Gao

et al. 2018

IEEJ Transactions Elec Engng

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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‐affinity immune cells from deletion by changing their receptor specificity realized the clonal selection process anew. By combining clonal selection theory and receptor editing, a quantum clonal selection algorithm based on complete receptor editing operation is proposed for the traveling salesman problem (TSP) and the holes‐machining‐path‐planning (HMPP) problem. Two receptor editing operators (inversion and deletion) work together to improve the performance of CSA. Furthermore, in order to overcome the drawback of asexual proliferation during the immune maturation process, a quantum interference crossover based on complete receptor editing operation is used. The effectiveness of the improved algorithm is evaluated on optimization problems including TSP and HMPP problems. The experimental results are also compared with those of other methods based on clonal selection theory. © 2018 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc.

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Section: Simulation and Discussionmentioning

confidence: 89%

Complete receptor editing operation based on quantum clonal selection algorithm for optimization problems

Dai

Gao

et al. 2018

IEEJ Transactions Elec Engng

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“…The power of GA lies in its ability to search for multipoints in parallel, not a single point [14,15]. Therefore, GA can find the global optimum quickly and avoid falling into a local optimum.…”

Section: Genetic Algorithmsmentioning

confidence: 99%

Application of neural networks to the study of the influence of diet and lifestyle on the value of bone mineral density in post-menopausal women

Juez

Suárez-Suárez

Lasheras³

et al. 2011

Mathematical and Computer Modelling

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a b s t r a c tOsteoporosis is characterized by low bone mineral density (BMD). This illness has a highcost impact in all developed countries. The aim of this article is the development of a mathematical method able to predict the BMD of post-menopausal women, taking into account only certain nutritional variables. This research applies neural networks for the study of the influence of diet and lifestyle on the value of bone mineral density in postmenopausal women.A questionnaire on nutritional habits and lifestyle was drawn up. The variables obtained from this, together with the BMD of the patients calculated by densitometry, were processed using genetic algorithms in order to reduce the number of input variables. Finally, a neural network model using only those variables considered important was applied.It has been proved to be possible to build a neural network model able to forecast the BMD of post-menopausal women according to their responses to the questionnaire. This model can be used to determine which women should take a densitometry in order to verify their bone quality and thus prevent some risks associated with osteoporosis.

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“…The related costs of the single drill puncher are as follows: In order to show the superiority of the method in the paper, we adopt the different classical methods to solve the problem. The classical methods mainly have the dynamic planning [8,9,10], the neural network [11,12,13], the simulation annealing [14,15,16] and the ant colony algorithm [17,18,19,20].…”

Section: ) Generate[p(n)] 2) Evaluate[p(h)] 3) Repeat Roof Generatiomentioning

confidence: 99%

Improving puncher efficiency using a double-loop traveling salesman problem

Wang

Feng

et al. 2013

2013 Ninth International Conference on Natural Computation (ICNC)

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Making the via holes is an important component part in the production of the printed circuit board. Therefore, how to improve the production efficiency of the puncher is a valuable research topic. In the paper, a novel mathematical model is built for the printed circuit board. Further more, we propose a novel method to solve the novel mathematical model. Furthermore, an improved double loop TSP model with the multiple constraint conditions is employed to solve the improving problem of the production efficiency. The experimental results show that our model can effectively improve the production efficiency of the puncher and the proposed method is more effectively than other traditional algorithms.

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Dynamic diversity control in genetic algorithm for mining unsearched solution space in TSP problems

Cited by 67 publications

References 21 publications

Complete receptor editing operation based on quantum clonal selection algorithm for optimization problems

Complete receptor editing operation based on quantum clonal selection algorithm for optimization problems

Application of neural networks to the study of the influence of diet and lifestyle on the value of bone mineral density in post-menopausal women

Improving puncher efficiency using a double-loop traveling salesman problem

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