Work

Rider Pressure in Intelligent Food Delivery Considering Dynamic Weather in Smart Cities

Year: 2025

Type: article

Abstract: To address the imbalance among riders, platforms, and merchants in food delivery within the context of Smart Cities, this study proposes an Intelligent Food Delivery model incorporating Dynamic Weather Conditions. A multi-objective optimization framework considering customer satisfaction, rider delivery pressure, and platform efficiency is established. An Improved Sparrow Search Algorithm (ISSA), enhanced by Sin-chaotic, Golden Sine, Adaptive t-distribution, and Dynamic Selection mechanisms, demonstrates superior convergence speed and accuracy. Simulations under Clear, Rainy, and Snowy scenarios validate ISSA's effectiveness in reducing rider pressure and optimizing delivery routes, providing robust theoretical guidance for intelligent logistics management in Smart Cities.

Source: International Journal of Swarm Intelligence Research

DOI: 10.4018/ijsir.389048

Authors: Shuai Huang, Zhipeng Zhang, Tianyu Fu

Institutions: China University of Labor Relations, University of Science and Technology Beijing, China University of Mining and Technology - Beijing

Language: English

Topic: Urban and Freight Transport Logistics

Subfield: Building and Construction

Field: Engineering

Domain: Physical Sciences

SDGs: Industry, innovation and infrastructure, Sustainable cities and communities

Open Access status: hybrid

OpenAlex ID: W4414459495

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