Hybrid Grey Wolf Optimizer for Vehicle Routing Problem with Multiple Time Windows

Li, Nan; Hu, Rong; Qian, Bin; Yu, Nai-Kang

doi:10.1007/978-3-030-84522-3_56

Cited by 2 publications

(3 citation statements)

References 13 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…It can be seen from equation ( 8) that the nonlinear strategy changes slowly in the early phase of the search, and its representative algorithm has a great global exploration capability; in the later stage of the search, σ changes quickly, and its representative algorithm will have good local search capability. Te control parameter σ expressed in equation ( 8) is simpler and easier to implement than the parameter selection method in [21]. Te convergence factor σ will show a nonlinear dynamic change law with the growth of evolutionary iterations number, and it can provide a compromise between global and local search capabilities.…”

Section: Improving the Gwo Algorithmmentioning

confidence: 99%

Abnormal Diagnosis Method of Self-Powered Power Supply System Based on Improved GWO-SVM

2023

Journal of Control Science and Engineering

View full text Add to dashboard Cite

In order to solve the problem of low abnormal diagnosis rate of self-powered power supply system, an improved grey wolf optimization-support vector machine (GWO-SVM) algorithm combined with maximal information coefficient (MIC) are proposed. First, the feature sets of 11 kinds of monitoring data are optimized and selected based on MIC for self-powered power supply system. By eliminating redundant variables and insensitive variables, feature variable sets with great influence on abnormal diagnosis are selected. Second, by upgrading the selection method of control parameter σ from linear to nonlinear, an improved GWO-SVM algorithm that can take into account both global and local search capabilities is proposed. Furthermore, the optimal feature set which has great influence on abnormal diagnosis is selected as the input of the proposed algorithm, and then the abnormal diagnosis method combining the improved GWO-SVM with MIC is constructed for self-powered power supply system. The specific algorithm flow and step are given. Finally, compared with other algorithm, the simulation experiments show that the GWO-SVM method has a higher accuracy and a higher recall rate for the abnormal diagnosis in the self-powered power supply system.

show abstract

Section: Improving the Gwo Algorithmmentioning

confidence: 99%

Abnormal Diagnosis Method of Self-Powered Power Supply System Based on Improved GWO-SVM

2023

Journal of Control Science and Engineering

View full text Add to dashboard Cite

show abstract

“…The distribution paths are initialized with clear values for fuzzy demands and they determine whether the vehicle will carry out material distribution through Credibility theory. [11][12][13][14] Furthermore, based on the traditional SSA, the local and the global search capabilities of the algorithm are enhanced by introducing improvement strategies such as the Cauchy variation, opposition-based learning, and adaptive strategy. The strategies also reduce the blindness of the algorithm while retaining its extensive search capability to solve the problem effectively.…”

Section: Introductionmentioning

confidence: 99%

“… 13 Li et al have similarly studied the VRP with multiple time windows under fuzzy demand and developed a two-stage hybrid optimization algorithm to solve the problem. 14 In a nutshell, the general distribution model can no longer meet the demand of emergency material distribution under major public health emergencies with serious social hazards such as COVID-19. For that, this paper focuses on the combination of fuzzy demand and emergency support material distribution problems to explore a realistic and feasible distribution model under the influence of COVID-19.…”

Section: Introductionmentioning

confidence: 99%

Optimization of urban emergency support material distribution under major public health emergencies based on improved sparrow search algorithm

Pan

Cao

et al. 2023

Science Progress

View full text Add to dashboard Cite

The outbreak of major public health emergencies such as the coronavirus epidemic has put forward new requirements for urban emergency management procedures. Accuracy and effective distribution model of emergency support materials, as an effective tool to inhibit the deterioration of the public health sector, have gradually become a research hotspot. The distribution of urban emergency support devices, under the secondary supply chain structure of “material transfer center-demand point,” which may involve confusing demands, is studied to determine the actual situation of fuzzy requests under the impact of an epidemic outbreak. An optimization model of urban emergency support material distribution, based on Credibility theory, is first constructed. Then an improved sparrow search algorithm, ISSA, was designed by introducing Sobol sequence, Cauchy variation and bird swarm algorithm into the structure of the classical SSA. In addition, numerical validation and standard test set validation were carried out and the experimental results showed that the introduced improved strategy effectively improved the global search capability of the algorithm. Furthermore, simulation experiments are conducted, based on Shanghai, and the comparison with existing cutting-edge algorithms shows that the designed algorithm has stronger superiority and robustness. And the simulation results show that the designed algorithm can reduce vehicle cost by 4.83%, time cost by 13.80%, etc. compared to other algorithms. Finally, the impact of preference value on the distribution of emergency support materials is analyzed to help decision-makers to develop reasonable and effective distribution strategies according to the impact of major public health emergencies. The results of the study provide a practical reference for the solution of urban emergency support materials distribution problems.

show abstract

Hybrid Grey Wolf Optimizer for Vehicle Routing Problem with Multiple Time Windows

Cited by 2 publications

References 13 publications

Abnormal Diagnosis Method of Self-Powered Power Supply System Based on Improved GWO-SVM

Abnormal Diagnosis Method of Self-Powered Power Supply System Based on Improved GWO-SVM

Optimization of urban emergency support material distribution under major public health emergencies based on improved sparrow search algorithm

Contact Info

Product

Resources

About