Table 1
Comparative analysis of different studies.
| References | Method/Model | Advantages | Limitations |
|---|---|---|---|
| Boujarra M et al. [10] | Deep learning integrated model (intelligent logistics optimization) | Improves inventory optimization and route planning, enhances data security | High complexity |
| Thuengnaitham A et al. [11] | Analytic hierarchy process | Systematically determines warehouse location criteria weights | Relies heavily on expert subjective judgment |
| Zhang P [12] | Stepwise site selection method (e-commerce logistics) | Improves efficiency, reduces costs, enhances competitiveness | Narrow application scenarios |
| Dağıstanlı H A et al. [13] | GIS + fuzzy comprehensive evaluation method (ammunition depot selection) | Emphasizes safety, considers environmental and personnel factors | Overly case-specific, poor generalizability; lacks distribution route optimization |
| Sohail A et al. [14] | Single GA algorithm | Suitable for complex large-scale problems | Prone to premature convergence, slow convergence speed |
| Muneer S M et al. [15] | GA-based feature selection model | Improves prediction accuracy | Application limited to classification and prediction |
| Tian J et al. [16] | Surrogate model-based PSO | Addresses high-dimensional, time-consuming problems | Application limited to classification and prediction |
| Yu Z et al. [17] | Improved PSO | Enhances global search ability, avoids local convergence | High practical implementation cost |
| This study | Hybrid PSO-GA optimization model | Combines GA's solution space diversity with PSO's global search capability | – |
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.