Journals
  Publication Years
  Keywords
Search within results Open Search
Please wait a minute...
For Selected: Toggle Thumbnails
Hybrid adaptive large neighborhood search algorithm for solving time-dependent vehicle routing problem in cold chain logistics
Zhihao XIAO, Zhihua HU, Lin ZHU
Journal of Computer Applications    2022, 42 (9): 2926-2935.   DOI: 10.11772/j.issn.1001-9081.2021071361
Abstract357)   HTML5)    PDF (1487KB)(148)       Save

Aiming at the problems of premature convergence and easily falling into local optimum in the adaptive large neighborhood search algorithms with single mechanism, a hybrid adaptive large neighborhood search algorithm was proposed to solve Time-Dependent Vehicle Routing Problem (TDVRP) in cold chain logistics. Firstly, the time-varying vehicle speed was described according to the continuous driving time dependent function, the real-time fuel consumption was evaluated by using the comprehensive fuel consumption model, and a routing optimization model with the goal of minimizing the total cost was established. Then, according to the NP (Non-deterministic Polynomial)-hard property and time-dependent characteristics of the problem, a variety of large neighborhood search operators for destroying and repairing solutions were designed, and the destroy-repair large neighborhood search operators were integrated into Artificial Bee Colony (ABC) algorithm to improve the global search ability of the algorithm. Simulation results show that compared with Adaptive Variable Neighborhood Search Elite Ant Colony (AVNS_EAC) algorithm, Adaptive Large Neighborhood Search Elite Ant Colony (ALNS_EAC) algorithm, Adaptive Large Neighborhood Search Elite Genetic (ALNS_EG) algorithm and Adaptive Large Neighborhood Search Simulated Annealing (ALNS_SA) algorithm, the proposed Adaptive Large Neighborhood Search Artificial Bee Colony (ALNS_ABC) algorithm has the optimal fitness values increased by 46.3%, 5.3%, 36.8% and 6% respectively and averagely on multiple test data groups. It can be seen that this algorithm has higher computational performance and stronger stability, and can provide a more reasonable decision-making basis for cold chain logistics enterprises to take into account economic and environmental benefits at the same time.

Table and Figures | Reference | Related Articles | Metrics
Prediction model of transaction pricing in internet freight transport platform based on combination of dual long short-term memory networks
Youzhi LI, Zhihua HU, Chun CHEN, Peibei YANG, Yajing DONG
Journal of Computer Applications    2022, 42 (5): 1616-1623.   DOI: 10.11772/j.issn.1001-9081.2021030504
Abstract257)   HTML10)    PDF (2220KB)(93)       Save

Prediction results of transaction pricing of transport service orders in internet freight transport platform are the direct reflections of both platform operation strategy and carrier decision, and influences both platform benefits and the healthy development of carrier market significantly. Taking internet freight transport platform of SF Express network as an example, the data were preprocessed through missing value processing and categorical data conversion. Aiming at the prediction precision problem of transaction pricing in internet freight transport platform, a new prediction model of transaction pricing in internet freight transport platform based on combination of dual Long Short-Term Memory networks(LSTM) was designed, and the prediction results were analyzed by K-means clustering. Compared with the models such as LSTM, Support Vector Regression (SVR), Long Short-Term-Memory combined with Support Vector Regression (LSTM-SVR), and combination of grey GM(1,1) and Back Propagation (BP) (GM(1,1)-BP), the combination model of dual LSTM has the lowest Mean Absolute Error (MAE), Mean Square Error (MSE), Mean Absolute Percentage Error (MAPE) and highest R square (R2), which is 9.90, 402.54, 1.48 and 0.999 97 respectively. The evaluation results of predicted order transaction pricing by using K-means clustering analysis are consistent with the actual values. Experimental results indicate that, the proposed combination model of dual LSTM has effectiveness and precise prediction effect of transaction pricing in internet freight transport platform.

Table and Figures | Reference | Related Articles | Metrics