Heuristic optimization is used to tune parameters in various scientific fields. Therefore, a successful optimization algorithm that must be able to evolve in a parsimonious manner in many situations is necessary. Ofte...
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Heuristic optimization is used to tune parameters in various scientific fields. Therefore, a successful optimization algorithm that must be able to evolve in a parsimonious manner in many situations is necessary. Often, heuristic optimization algorithms are inspired by nature but imperialist competitive algorithm, inspired by the laws and policies governing human society, was presented in recent decade. Imperialist competitive algorithm was applied in various fields. This algorithm had a very good performance compared to other optimization algorithms. For this reason, this study tries to modify imperialist competitive algorithm for improve the accuracy and performance of the algorithm. Assimilation operator of the imperialist competitive algorithm is modified. The main motivation of this work is to introduce a powerful heuristic optimization algorithm. A comparison between the proposed imperialist competitive algorithm framework and several versions imperialist competitive algorithm on 6 standard numerical benchmarks and four famous optimization algorithm indicate that the proposed algorithm has a good performance on a wide variety of problems.
Aiming at the reliability optimization algorithm based on wireless sensor network, a data fusion algorithm based on extreme learning machine for wireless sensor network was proposed according to the temporal spatial c...
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Aiming at the reliability optimization algorithm based on wireless sensor network, a data fusion algorithm based on extreme learning machine for wireless sensor network was proposed according to the temporal spatial correlation in data collection process. After analyzing the principles, design ideas and implementation steps of extreme learning machine algorithm, the performance and results were compared with traditional BP algorithm, LEACH algorithm and RBF algorithm in simulation environment. The simulation results showed that the data fusion optimization algorithm based on the limit learning machine for wireless sensor network was reliable. It improved the efficiency of fusion and the comprehensive reliability of the network. Thus, it can prolong the life cycle and reduce the total energy consumption of the network.
In recent years, digital technology has been used in all aspects of peoples work and life more and more frequently and has exerted a certain impact on the design of buildings. More and more architectural design teams ...
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In recent years, digital technology has been used in all aspects of peoples work and life more and more frequently and has exerted a certain impact on the design of buildings. More and more architectural design teams add mathematical logic and digital technology to the early stages of their design to better control the design work and implement the construction. Digital building design mainly includes parametric design and algorithm generation design, the former of which is mainly studied in this paper. As a modeling design algorithm which puts an emphasis on logic and reason, parametric design emphasizes the scientific nature of architectural design. In order to achieve the optimal design of the combination of building physics, institutional performance and parameterization, this paper applies the Dijkstra algorithm and the most energy efficient scheme generation (MEESG) energy consumption prediction method to the optimization design of wiring and performance and achieves good results, suggesting that the parameter optimization algorithm has a good impetus to the design of digital building.
In order to improve the accuracy and the convergence speed of the sphericity error, an improved teaching and learning algorithm is proposed to evaluate the sphericity error. Based on the basic teaching-learning-based ...
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In order to improve the accuracy and the convergence speed of the sphericity error, an improved teaching and learning algorithm is proposed to evaluate the sphericity error. Based on the basic teaching-learning-based optimization, the initial solution quality is improved by logistic chaotic initialization;At the end of each iteration, the interpolation algorithm is applied to the global optimal solution to further improve the search accuracy of the algorithm. Finally, one group of sphericity error algorithm though the measurement data in the related literature is verified the effectiveness of the ITLBO, the test result show that the ITLBO algorithm has advantages in the calculating accuracy and iteration convergence speed, and it is very suitable for the application in the sphericity error evaluation.
SMEs play an increasingly important role in promoting national economic development and social progress. With increasingly fierce market competition, the challenges faced by SMEs are gradually increasing, and it is ur...
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SMEs play an increasingly important role in promoting national economic development and social progress. With increasingly fierce market competition, the challenges faced by SMEs are gradually increasing, and it is urgently needed to improve logistics management to increase the economic benefits of enterprises. Although SMEs are not strong in strength, the impact of logistics activities on companies continues to increase, and companies must also pay attention to logistics construction. This paper elaborates the problems existing in SMEs in light of the major problems in the logistics management of SMEs, and analyzes the optimization algorithms of logistics management to lay a solid foundation for further development.
This paper studies the optimization problem of PCB assembly time for multi-head placement machine. Mathematical model is built and analyzed for the problem, which is of a combinatorial nature and computationally intra...
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ISBN:
(纸本)9781538629185
This paper studies the optimization problem of PCB assembly time for multi-head placement machine. Mathematical model is built and analyzed for the problem, which is of a combinatorial nature and computationally intractable. An optimization algorithm based on heuristic strategy and scatter search method is proposed to minimize the PCB assembly time. By relaxing the restrictions on the problem, the algorithm reduces the assembly time by minimizing cycles of pick-and-place, constructing the simultaneous pickups and optimizing sequence of pick-and-place of components. Numerical experiments were conducted to evaluate the proposed algorithm, along with a comparison with a heuristic algorithm(HA) under strong constraints proposed in existed literature. The results show that the proposed algorithm has better performance in optimization results and can shorten PCB assembly time of multi-head placement machine effectively.
For the irregular nesting problem widely existing in modern manufacturing industry, this paper makes a research on it and presents an optimization algorithm based on no-fit polygon（NFP） method and hybrid heuristic s...
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ISBN:
(纸本)9781538629185
For the irregular nesting problem widely existing in modern manufacturing industry, this paper makes a research on it and presents an optimization algorithm based on no-fit polygon（NFP） method and hybrid heuristic strategy to solve it. The proposed algorithm first uses the composition method of trace line segment to calculate no-fit polygons（NFPs） between every two pieces in piece set, and extracts the candidate placement points for a candidate piece to be placed by using generated NFPs in combination with internal no-fit polygon（INFP） between the piece and the material plate. Then, the algorithm designs and applies three hybrid heuristic strategies to evaluate all candidate pieces and choose the best piece to place next and determine the best placement point for the selected piece. Experimental test has been performed to verify feasibility and effectiveness of the proposed algorithm. The test results show that the algorithm can solve the irregular nesting problem effectively, and improve the utilization of material to a certain extent.
Aiming at the the poor local search capability of Particle Swarm optimization(PSO) algorithm, a hybrid particle swarm optimization algorithm is proposed. Firstly, the population is initialized by tent chaotic map to i...
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ISBN:
(纸本)9781509063529
Aiming at the the poor local search capability of Particle Swarm optimization(PSO) algorithm, a hybrid particle swarm optimization algorithm is proposed. Firstly, the population is initialized by tent chaotic map to improve the diversity of the initial population. In the evolution process, the tabu search strategy is adopted to improve algorithm convergence rate. Combining the chaos optimization strategy, this algorithm could jump out of local optimization and improve the local search ability. The simulation results of constrained optimization problems are reported and compared with the typical PSO algorithm. Simulation results show that this algorithm could effectively avoid local optimization, have good global search ability and local search ability.
Many optimization algorithms proposed for PCB assembly problem had a common problem that they introduced strong constraints, which made optimization performance deteriorate in practice. Focusing on component pick and ...
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ISBN:
(纸本)9789881563910
Many optimization algorithms proposed for PCB assembly problem had a common problem that they introduced strong constraints, which made optimization performance deteriorate in practice. Focusing on component pick and placement sequencing problem for multi-head placement machine in PCB assembly, this paper discuss some strong constraints involved in related optimization problem and propose an algorithm under relaxed constraints for problem solving. Certain strong constraints were relaxed for the algorithm to expand solution space, making it possible to find better solutions. Under such relaxation, an optimization algorithm based on scatter search (SS) method was constructed to solve the component sequencing problem, and steps of algorithm are detailed in the paper. Numerical experiments were made to conduct an evaluation for the proposed algorithm, along with a comparison with two heuristic algorithms proposed in other literatures. The results show that the proposed algorithm has better performance in optimization results and can shorten PCB assembly time of the placement machine effectively.
With the rapid development of economy and science and technology in our country, the types and quantities of various optimization problems have increased in large scale, and the optimization of the model structure can...
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With the rapid development of economy and science and technology in our country, the types and quantities of various optimization problems have increased in large scale, and the optimization of the model structure can improve the efficiency. Based on this, the group intelligent optimization algorithm and its evaluation were studied. The intelligent homogenization partition was introduced first, and then the calculation of the cluster intelligent alignment probabilities was introduced, and the optimization process of the last group intelligent optimization algorithm was described in detail. The test results show that the optimization model of group intelligent optimization algorithm has more realistic and reasonable application.
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