A Macro-to-Micro Layout Optimization Scheme for Functional Interwoven Areas of Commercial Complex
Bibliographic Data
| ID | 22107302 |
|---|---|
| Authors | Jingxuan Peng (0000-0002-2772-0564, Beijing University of Technology), Zhonghua Wei (0000-0003-1459-0526, Beijing University of Technology), Xueying Tong (0009-0000-8092-0701, Beijing University of Technology), Xuwen Jia (0009-0005-0478-1195, University College London), Yanyan Chen (0000-0002-7198-6044, Beijing University of Technology), Yongxing Li (0000-0002-4493-8119, Beijing University of Technology), Fujiyama Taku (0000-0002-5986-5346, University College London) |
| Year | 2026 |
| Pages | 1-19 |
| Publication date | 2026-01-01 |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | IEEE Transactions on Computational Social Systems (JOURNAL) |
| Journal identifiers | ISSN: 2329-924X • E-ISSN: 2373-7476 |
| Publisher | Institute of Electrical and Electronics Engineers (IEEE) (PUBLISHER) |
| DOI | 10.1109/tcss.2025.3644359 |
| OpenAlex | W7117887854 |
| Language | EN |
In commercial complexes, the functional interwoven areas (FIA) with multiple attributes shops accommodate diverse population of pedestrians with heterogeneous travel purposes. A well-designed layout scheme of FIA can effectively increase the revenue while reduce the pedestrian congestion. However, existing layout schemes are more developed from the operator’s perspective, focusing on maximizing rents while neglecting shop attributes and pedestrians heterogeneity, which results in excessive corridor congestion and suboptimal store visit rates. To address these issues, this article proposes a novel macro-to-micro layout optimization framework that enhances pedestrian in-store rate while mitigating internal congestion. The proposed framework consists of two stages: 1) a macrolevel optimization model which generates multiple feasible layout schemes by using shop attributes based attractiveness algorithm; and 2) a microlevel simulation model which evaluates pedestrian movement dynamics and corridor density under different layouts by integrating an attractive potential based social force model (AP-SFM). Based on parameters calibrated from real collected data, we conduct extensive numerical and simulation experiments across two distinct commercial complexes: 1) China World Mall (CWM); and 2) Shin Kong Place (SKP). The results demonstrate that the optimized layouts significantly increase pedestrian in-store rates while effectively reducing average corridor density and alleviating local congestion, without altering the total pedestrian volume. Furthermore, the successful application in two distinct commercial complexes proves the validity, rationality, and generality of the proposed framework. Our research effectively integrates shop diversity and pedestrian heterogeneity into shop layout optimization, providing a practical and scalable decision-support tool for layout design and management
Deck · Generality · Multi-objective optimization · Page layout · Pedestrian · Revenue · Scalability · Advanced Manufacturing and Logistics Optimization · Consumer Retail Behavior Studies · Urban and Freight Transport Logistics
| Highly cited | No |
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