In this study, a hybrid of quantumevolutionary and Artificial Immune algorithms (QIA) is proposed for solving Multiobjective Flexible Job Shop Scheduling Problem (MFJSSP). This problem is formulated as three-objectiv...
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In this study, a hybrid of quantumevolutionary and Artificial Immune algorithms (QIA) is proposed for solving Multiobjective Flexible Job Shop Scheduling Problem (MFJSSP). This problem is formulated as three-objective problem which minimizes completion time (makespan), critical machine workload and total work load of all machines. The quantum coding is shown to improve the immune strategy. The proposed algorithm overcomes the problem by increasing the speed of convergence and diversity of population. Three benchmarks of Kacem and Brandimart are examined to evaluate the performance of the proposed algorithm. The experimental results show a better performance in comparison to other approaches.
A novel quantum evolutionary algorithm based immune mechanism for solving multi-objective public traffic optimization (PRIQEA) is proposed. By niche methods population is divided into subpopulations of real-coded chro...
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ISBN:
(纸本)9781424417339
A novel quantum evolutionary algorithm based immune mechanism for solving multi-objective public traffic optimization (PRIQEA) is proposed. By niche methods population is divided into subpopulations of real-coded chromosome automatically, and then local search is carried by the immune mechanism, each subpopulation can obtain optimal solution. By exchanging optimal pattern between subpopulations, we can achieve co-evolutionary of niche. Real-coded chromosome is provided with innovation;co-evolutionary strategy of niche can guarantee quite nicely the population diversity and the convergence speed The convergence of the PRIQEA is proved based on Markov chain;the algorithm is applied to urban public traffic operation optimization, and experimental results show its superiority.
Cosmetics is necessary for everyone’s daily live,its impact on economy can not be ignored,but severe inventory stacking and lacking problems still ***,the occurrence of these problems is likely to be decreased via fo...
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Cosmetics is necessary for everyone’s daily live,its impact on economy can not be ignored,but severe inventory stacking and lacking problems still ***,the occurrence of these problems is likely to be decreased via forecasting demand ***,an Aggregated Forecast Through Exponential Re-weighting-Improved quantum evolutionary algorithm (AFTER-IQEA) forecasting model is developed in this *** influential factors are chosen by Gray Relation Analysis,while considering the seasonal factor by Winter’s exponential *** models: Evolving Neural Network (ENN),Adaptive Network-based Fuzzy Inference System (ANFIS),and Particle Swarm Optimization Wavelet v-Support Vector Machine (PSOWv-SVM) are used to forecast separately,and then integrate into AFTER-IQEA by dynamic weights generated from AFTER *** effectiveness of the proposed approach is demonstrated using real-world data,and it is superior to other traditional statistical models and neural network.
With the wide application of flexible AC transmission system(FACTS) in power system,one of the major directions of FACTS development is the research of multi-FACTS coordinated control(MFCC) based on wide-area measurem...
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With the wide application of flexible AC transmission system(FACTS) in power system,one of the major directions of FACTS development is the research of multi-FACTS coordinated control(MFCC) based on wide-area measurement system(WAMS).Since time-delay is unavoidable in WAMS,this study concentrates on the anti-delay coordinated control algorithm based on free-weighting matrix approach which utilizes the output feedback signals from *** taking time delay into consideration,the proposed algorithm ensures the minimum ratio of time-delay system,and the optimal gain of MFCC can be obtained through the quantumevolutionary *** validity and applicability of the proposed coordinated control algorithm is demonstrated in a four-machine,two-area system.
It was indicated from the recent research that quantum Genetic algorithm(QGA) outperformed conventional genetic algorithm in its lower running time and ability of finding better solution when it solved a class of nume...
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It was indicated from the recent research that quantum Genetic algorithm(QGA) outperformed conventional genetic algorithm in its lower running time and ability of finding better solution when it solved a class of numerical and knapsack of combinatorial optimization problems. However, with qutbit of quantum individual interfering, parameter γ of the termination criterion is difficult to determine. The rotate gate which can promote the population is difficult to change its state of qutbit, and this phenomenon often induces premature. To improve the performance of the QGA, a controllable rotate gate and a new termination criterion are proposed in this paper. The controllable rotation gate can induce the convergence of qutbit not only to either 0 or 1, but also to either ε or 1 - ε, and make the proposed algorithm to escape the local optimum. Based on gathering factor and qutbit convergence factor, a new termination criterion is proposed. The qutbit decreases the impact on parameter γ, and the new terminate criterion can efficiently control the relation of better solution and its running time. In addition, the Simplex method is introduced as a local searching scheme, which greatly improves the performance of algorithm. At last, the global convergence of the proposed algorithm is proved in theory, and comparable numerical experiments show that the proposed algorithm is more powerful than the compared algorithm in solution quality and speed.
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