According to the perishable characteristics of refrigerated food and the objective of minimizing the total cost, the mathematical optimization model of cold chain logistics distribution center location problem is established by introducing such constraints as the freshness and time window. In order to solve the problems of slow convergence and easy to fall into local optimal solution in the process of the traditional wolf colony optimization, an immune wolf colony hybrid algorithm is proposed to solve the location problem of distribution center. In this hybrid algorithm, the idea of vaccination of immune algorithm is introduced into the wolf colony algorithm. By adjusting the antibody concentration and selecting immune operator, the diversity of the wolf colony algorithm is improved, and then the search space of the solution is expanded; the convergence speed and solution accuracy of the wolf colony algorithm are improved by using immune memory cells and immune vaccine. The simulation results show that the immune wolf colony algorithm can quickly converge to the global optimal solution and optimize the location model of logistics distribution center. The algorithm has good feasibility and robustness. INDEX TERMS Cold chain logistics, distribution center location, immune algorithm, wolf colony algorithm.
This study analyses consumer last-mile delivery service choice behaviour by developing a cross-nested logit model (CNL); we then compare the analytical results with three nested logit models (NL). The model parameters are estimated using the data from a questionnaire collected from consumers residing in Beijing, Shanghai, Tianjin, Guangdong, Zhejiang, Jiangsu, and Shandong. The direct elasticities and cross-elasticities are then calculated to assess the change in probability of each alternative caused by utility variables. Parameter estimation results demonstrate that the CNL model outperforms the three NL models. Consumers are usually reluctant to change the way they are served when utility variables are altered. Moreover, elasticity analysis results suggest that service factors have the strongest effect on choice probability, followed by socioeconomic factors and delivery activity factors. Thus, enterprises should first strive to promote the service experience of consumers in corresponding delivery services, then account for the effect of socioeconomic factors, and finally consider changing delivery service fees if they want to induce consumers to select a specified delivery service.INDEX TERMS Last mile, delivery service, nested logit, cross-nested logit.
Purpose: This paper is committed to design a logistics industry development policy model based on system dynamic to simulate the policy measures which promote region economic and logistics efficiency. The interaction between logistic industry development policy and economy needs to be investigated and the influence degree of logistic efficiency affected by industry policy needs to be identified too.Design/methodology/approach: In order to achieve the objective, it makes a system analysis from industry perspective to divide system into economic growth subsystem, logistics demand subsystem and logistics supply subsystem. Then the hypothesis and the boundaries are defined, and the causal diagram and system flow diagrams are drawn. The paper designs parameters and structural equation by the sample of Beijing using the econometrics model and takes model validation. Taking Beijing as an example, logistics industry development policy is simulated from the aspect of technological progress, increasing fixed assets investment, adjusting the industrial structure proportion and comprehensive policy by changing the parameters using Vensim-PLE. Findings:After logistics development policy is highly simulated by system dynamic model of logistics industry development policy, it is found that the policies of technological progress, fixed assets investment increasing, the industrial structure proportion adjustment and the -573-Journal of Industrial Engineering and Management -http://dx.doi.org/10.3926/jiem.1036 comprehensive policy have different function to affect GDP, logistics demand, supply capacity and actual logistics costs.Originality/value: Compared with the previous research, this paper analyzes the interactive mechanism between logistics industry policy and region economy from a system perspective and establishes system dynamics model of logistics industry development policy to make up for the limitation of previous research.
Aiming at the nonlinear and non-stationarity of gearbox fault signals and the confusion among different fault categories, a gear fault diagnosis method combining variational mode decomposition, reconstruction and ResNeXt is proposed in this paper. In this paper, parameter K of VMD is determined according to the changing trend of sample entropy (SE), K modal components are obtained after decomposition, and the effective modal components are extracted and reconstructed according to Pearson autocorrelation coefficient, so as to remove redundant information from the original signal. Then the reconstructed signal is transformed by time–frequency and output two-dimensional time–frequency information, which is used as the input of ResNeXt model to extract the characteristics of different faults. Moreover, the model performance is improved by changing the learning rate decline rate, and a fault diagnosis model with high precision and good stability is established.
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