Parameters setting is an important problem of evolution algorithms,including differential evolution algorithm.It has an effect on the performance of evolution algorithms.According to the problem of parameters of differential evolution,a method is presented,which uses self-adaptive as a scientific evidence to adjust parameters and set F and CR combined with modulated probability.An algorithm is presented,which depends on the fitness of individual and modulated probability set the parameters F and CR automatically.This method can get the optimal control parameters for different optimization problem without user interaction.Moreover,two trial vectors are created by recombination for increased colony diversity and avoided premature convergence.These vectors compete with the parent individual to be the next generation.Experimental results indicate that the proposed algorithm is efficient and feasible.It is superior to other related methods such as DE,jDE,FADE,MPDE,DDE both on the quality of solution and on the convergence rate,especially for high dimension functions.

Self-adapting control parameters in differential evolution

A modified differential evolution algorithm was presented.In the proposed algorithm,the difference vector,which is employed in mutating each individual by simple differential evolution algorithm,was recorded.Each mutated individual was taken as the center of a neighborhood,the corresponding difference vector as radius.The modification increased the local searching ability of differential evolution algorithm.The numerical experiments and simulations of typical multimodal function optimization showed that the modified algorithm converged faster than differential evolution algorithm,and also held the good global searching ability.

Modified Differential Evolution Algorithm and Its Application in Function Optimization

Most of Tibetan-style ancient structures are age-old,and there are no design drawings in the construction process,so a lot of uncertain factors may appear in the structural analysisThe results obtained by finite element analysis usually can not be in good agreement with experimental resultsWhen the error between them is larger,the dynamic characteristics of the structural model acquired by the finite element method and the actual measurement may have greater discrepancy,even beyond the engineering precision required in practiceThe finite element model of the measured structure was modified to make it closer to the true state by using the artificial neural network(ANN) methodIn the method,the measured modal parameters were adopted as the target to update some uncertain factors of the finite element model of a typical Tibetan structure,such as the height of equivalent non-uniform beam,the material density and the elastic modulusThe finite element model after updating is significant for damage identification and reliability assessment of typical Tibetan structures

Finite element model updating of tibetan structure based on artificial neural network

By formulating the problem of minimizing the makespan on a single batch machine with non-identical job sizes as a problem of minimizing the wasted space minimization, a candidate set strategy is designed to narrow the search space when constructing the batches, combined with a heuristic based on the wasted space to update the pheromone information.Incorporated with a local optimization method to further improve the performance, an improved max-min ant system algorithm is presented. Moreover, the parameter setting in the proposed algorithm is analyzed by experimental designs to determine the appropriate parameter values. The simulation results show the effectiveness and robustness of the proposed algorithm that outperforms several previously studied algorithms.

Improved ant colony algorithm for solving batch scheduling problem with non-identical job sizes

In order to solve the problem of global optimization, a new optimization method based on the law of universal gravitation is proposed, which is a random search algorithm derived from the simulation of natural imagination, which belongs to the category of evolutionary computation and is a new intelligent optimization algorithm. This method abstracts the global optimal value into a "black hole" in the universe, and other free celestial bodies in the universe approach the "black hole" by gravitational force, and are eventually "swallowed" by the black hole. The direction and step of the algorithm iteration are deduced through the formula of gravitation, which reduces the influence of the stochastic factors on the algorithm and improves the efficiency of the optimization calculation. Through numerical experiments, it is proved that the performance of the algorithm in global convergence and computing speed is superior to other optimization algorithms in the relevant literatures, and the specular reflection algorithm is also proven to be an effective and reliable optimization tool when solving high-dimensional optimization problems. It is applied to the optimization design of crank and rocker mechanism, and the calculation result further affirms the value of the algorithm in the field of engineering calculation. Keywords—global optimization; gravitation; numerical experiments; crank rocker

/pdf/research-on-new-intelligent-optimization-algorithm-based-on-2psyqtbvz7.pdf

Research on New Intelligent Optimization Algorithm Based on the Law of Universal Gravitation

The paper is built around the theme of community and culture revitalization, and our object of study is Qingshan Village-the site which the government has put both enormous investments and expectations in. However, wishes still haven’t transformed into realities as we discover several questions during our visit to the village: lack of connection between two generations of villagers, ineffective advertisement, and villagers’ indifference in terms of spreading their franchises, all of which have directly led to the village’s failures to perform its duty given by the government. To comprehend the phenomenon from more in-depth perspectives, the paper will first analyze the causes of these problems through existing theories. Then, combining the findings with the actual condition of the village, and eventually raise a proposal that is both applicable to Qingshan Village and other similar cases.

The Path Analysis of the Local Development of Culture & Tourism Industry Based on Old & New Citizens’ Integration: ——Taking Qingshan Village as An Example

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Research on New Intelligent Optimization Algorithm Based on the Law of Universal Gravitation

The Path Analysis of the Local Development of Culture & Tourism Industry Based on Old & New Citizens’ Integration: ——Taking Qingshan Village as An Example