A contribution-guided discrete differential evolution algorithm for the quadratic multiple knapsack problem

2016 ◽  
Author(s):  
Xiangling Zhao ◽  
Yun Dong ◽  
Lixin Tang
Keyword(s):  
Differential Evolution ◽  
Knapsack Problem ◽  
Differential Evolution Algorithm ◽  
Multiple Knapsack Problem ◽  
Evolution Algorithm ◽  
Multiple Knapsack ◽  
Discrete Differential Evolution

scholarly journals WSNs Compressed Sensing Signal Reconstruction Based on Improved Kernel Fuzzy Clustering and Discrete Differential Evolution Algorithm

2019 ◽  
Vol 2019 ◽  
pp. 1-9
Author(s):  
Zhou-zhou Liu ◽  
Shi-ning Li
Keyword(s):  
Compressed Sensing ◽  
Differential Evolution ◽  
Fuzzy Clustering ◽  
Clustering Algorithm ◽  
Signal Reconstruction ◽  
Differential Evolution Algorithm ◽  
Reconstruction Algorithm ◽  
Reconstruction Algorithms ◽  
Evolution Algorithm ◽  
Discrete Differential Evolution

To reconstruct compressed sensing (CS) signal fast and accurately, this paper proposes an improved discrete differential evolution (IDDE) algorithm based on fuzzy clustering for CS reconstruction. Aiming to overcome the shortcomings of traditional CS reconstruction algorithm, such as heavy dependence on sparsity and low precision of reconstruction, a discrete differential evolution (DDE) algorithm based on improved kernel fuzzy clustering is designed. In this algorithm, fuzzy clustering algorithm is used to analyze the evolutionary population, which improves the pertinence and scientificity of population learning evolution while realizing effective clustering. The differential evolutionary particle coding method and evolutionary mechanism are redefined. And the improved fuzzy clustering discrete differential evolution algorithm is applied to CS reconstruction algorithm, in which signal with unknown sparsity is considered as particle coding. Then the wireless sensor networks (WSNs) sparse signal is accurately reconstructed through the iterative evolution of population. Finally, simulations are carried out in the WSNs data acquisition environment. Results show that compared with traditional reconstruction algorithms such as StOMP, the reconstruction accuracy of the algorithm proposed in this paper is improved by 36.4-51.9%, and the reconstruction time is reduced by 15.1-31.3%.

A Novel Discrete Differential Evolution Algorithm for SVRPSPD

2013 ◽  
Vol 303-306 ◽  
pp. 2227-2230 ◽  
Author(s):  
Ling Juan Hou ◽  
Zhi Jiang Hou
Keyword(s):  
Genetic Algorithm ◽  
Differential Evolution ◽  
Vehicle Routing ◽  
Differential Evolution Algorithm ◽  
Computational Simulations ◽  
Special Design ◽  
Stochastic Vehicle Routing ◽  
Evolution Algorithm ◽  
Discrete Differential Evolution ◽  
Discrete Domain

Aiming at the stochastic vehicle routing problems with simultaneous pickups and deliveries, a novel discrete differential evolution algorithm is proposed for routes optimization. The algorithm can directly be used for the discrete domain by special design. Computational simulations and comparisons based on a medium-sized problem of SVRPSPD is provided. Results demonstrate that the proposed algorithm obtains better results than the basic differential evolution algorithm and the existing genetic algorithm.

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