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  • Open Access

    ARTICLE

    An Improved Multi-Actor Hybrid Attention Critic Algorithm for Cooperative Navigation in Urban Low-Altitude Logistics Environments

    Chao Li1,3,#, Quanzhi Feng1,3,#, Caichang Ding2,*, Zhiwei Ye1,3

    CMC-Computers, Materials & Continua, Vol.84, No.2, pp. 3605-3621, 2025, DOI:10.32604/cmc.2025.063703 - 03 July 2025

    Abstract The increasing adoption of unmanned aerial vehicles (UAVs) in urban low-altitude logistics systems, particularly for time-sensitive applications like parcel delivery and supply distribution, necessitates sophisticated coordination mechanisms to optimize operational efficiency. However, the limited capability of UAVs to extract state-action information in complex environments poses significant challenges to achieving effective cooperation in dynamic and uncertain scenarios. To address this, we presents an Improved Multi-Agent Hybrid Attention Critic (IMAHAC) framework that advances multi-agent deep reinforcement learning (MADRL) through two key innovations. Firstly, a Temporal Difference Error and Time-based Prioritized Experience Replay (TT-PER) mechanism that dynamically adjusts… More >

  • Open Access

    ARTICLE

    Lightweight Deep Learning Model and Novel Dataset for Restoring Damaged Barcodes and QR Codes in Logistics Applications

    Tarek Muallim1, Haluk Kucuk2,*, Muhammet Bareket1, Metin Kahraman1

    CMES-Computer Modeling in Engineering & Sciences, Vol.143, No.3, pp. 3557-3581, 2025, DOI:10.32604/cmes.2025.064733 - 30 June 2025

    Abstract This study introduces a lightweight deep learning model and a novel synthetic dataset designed to restore damaged one-dimensional (1D) barcodes and Quick Response (QR) codes, addressing critical challenges in logistics operations. The proposed solution leverages an efficient Pix2Pix-based framework, a type of conditional Generative Adversarial Network (GAN) optimized for image-to-image translation tasks, enabling the recovery of degraded barcodes and QR codes with minimal computational overhead. A core contribution of this work is the development of a synthetic dataset that simulates realistic damage scenarios frequently encountered in logistics environments, such as low contrast, misalignment, physical wear,… More >

  • Open Access

    ARTICLE

    Modeling of CO2 Emission for Light-Duty Vehicles: Insights from Machine Learning in a Logistics and Transportation Framework

    Sahbi Boubaker1,*, Sameer Al-Dahidi2, Faisal S. Alsubaei3

    CMES-Computer Modeling in Engineering & Sciences, Vol.143, No.3, pp. 3583-3614, 2025, DOI:10.32604/cmes.2025.063957 - 30 June 2025

    Abstract The transportation and logistics sectors are major contributors to Greenhouse Gase (GHG) emissions. Carbon dioxide (CO2) from Light-Duty Vehicles (LDVs) is posing serious risks to air quality and public health. Understanding the extent of LDVs’ impact on climate change and human well-being is crucial for informed decision-making and effective mitigation strategies. This study investigates the predictability of CO2 emissions from LDVs using a comprehensive dataset that includes vehicles from various manufacturers, their CO2 emission levels, and key influencing factors. Specifically, six Machine Learning (ML) algorithms, ranging from simple linear models to complex non-linear models, were applied under… More >

  • Open Access

    ARTICLE

    A 3-Dimensional Cargo Loading Algorithm for the Conveyor-Type Loading System

    Hyeonbin Jeong1, Young Tae Ryu2, Byung Duk Song1,*, Sang-Duck Lee3,*

    CMES-Computer Modeling in Engineering & Sciences, Vol.142, No.3, pp. 2739-2769, 2025, DOI:10.32604/cmes.2025.061639 - 03 March 2025

    Abstract This paper proposes a novel cargo loading algorithm applicable to automated conveyor-type loading systems. The algorithm offers improvements in computational efficiency and robustness by utilizing the concept of discrete derivatives and introducing logistics-related constraints. Optional consideration of the rotation of the cargoes was made to further enhance the optimality of the solutions, if possible to be physically implemented. Evaluation metrics were developed for accurate evaluation and enhancement of the algorithm’s ability to efficiently utilize the loading space and provide a high level of dynamic stability. Experimental results demonstrate the extensive robustness of the proposed algorithm More >

  • Open Access

    ARTICLE

    Secure Digital Image Watermarking Technique Based on ResNet-50 Architecture

    Satya Narayan Das1,2,*, Mrutyunjaya Panda2,*

    Intelligent Automation & Soft Computing, Vol.39, No.6, pp. 1073-1100, 2024, DOI:10.32604/iasc.2024.057013 - 30 December 2024

    Abstract In today’s world of massive data and interconnected networks, it’s crucial to burgeon a secure and efficient digital watermarking method to protect the copyrights of digital content. Existing research primarily focuses on deep learning-based approaches to improve the quality of watermarked images, but they have some flaws. To overcome this, the deep learning digital image watermarking model with highly secure algorithms is proposed to secure the digital image. Recently, quantum logistic maps, which combine the concept of quantum computing with traditional techniques, have been considered a niche and promising area of research that has attracted… More >

  • Open Access

    ARTICLE

    A Proposed Feature Selection Particle Swarm Optimization Adaptation for Intelligent Logistics—A Supply Chain Backlog Elimination Framework

    Yasser Hachaichi1, Ayman E. Khedr1, Amira M. Idrees2,*

    CMC-Computers, Materials & Continua, Vol.79, No.3, pp. 4081-4105, 2024, DOI:10.32604/cmc.2024.048929 - 20 June 2024

    Abstract The diversity of data sources resulted in seeking effective manipulation and dissemination. The challenge that arises from the increasing dimensionality has a negative effect on the computation performance, efficiency, and stability of computing. One of the most successful optimization algorithms is Particle Swarm Optimization (PSO) which has proved its effectiveness in exploring the highest influencing features in the search space based on its fast convergence and the ability to utilize a small set of parameters in the search task. This research proposes an effective enhancement of PSO that tackles the challenge of randomness search which… More >

  • Open Access

    ARTICLE

    Optimal Scheduling of Multiple Rail Cranes in Rail Stations with Interference Crane Areas

    Nguyen Vu Anh Duy, Nguyen Le Thai, Nguyen Huu Tho*

    Intelligent Automation & Soft Computing, Vol.39, No.1, pp. 15-31, 2024, DOI:10.32604/iasc.2024.038272 - 29 March 2024

    Abstract In this paper, we consider a multi-crane scheduling problem in rail stations because their operations directly influence the throughput of the rail stations. In particular, the job is not only assigned to cranes but also the job sequencing is implemented for each crane to minimize the makespan of cranes. A dual cycle of cranes is used to minimize the number of working cycles of cranes. The rail crane scheduling problems in this study are based on the movement of containers. We consider not only the gantry moves, but also the trolley moves as well as More >

  • Open Access

    ARTICLE

    Using Improved Particle Swarm Optimization Algorithm for Location Problem of Drone Logistics Hub

    Li Zheng, Gang Xu*, Wenbin Chen

    CMC-Computers, Materials & Continua, Vol.78, No.1, pp. 935-957, 2024, DOI:10.32604/cmc.2023.046006 - 30 January 2024

    Abstract Drone logistics is a novel method of distribution that will become prevalent. The advantageous location of the logistics hub enables quicker customer deliveries and lower fuel consumption, resulting in cost savings for the company’s transportation operations. Logistics firms must discern the ideal location for establishing a logistics hub, which is challenging due to the simplicity of existing models and the intricate delivery factors. To simulate the drone logistics environment, this study presents a new mathematical model. The model not only retains the aspects of the current models, but also considers the degree of transportation difficulty… More >

  • Open Access

    ARTICLE

    Hybrid Algorithm-Driven Smart Logistics Optimization in IoT-Based Cyber-Physical Systems

    Abdulwahab Ali Almazroi1,*, Nasir Ayub2

    CMC-Computers, Materials & Continua, Vol.77, No.3, pp. 3921-3942, 2023, DOI:10.32604/cmc.2023.046602 - 26 December 2023

    Abstract Effectively managing complex logistics data is essential for development sustainability and growth, especially in optimizing distribution routes. This article addresses the limitations of current logistics path optimization methods, such as inefficiencies and high operational costs. To overcome these drawbacks, we introduce the Hybrid Firefly-Spotted Hyena Optimization (HFSHO) algorithm, a novel approach that combines the rapid exploration and global search abilities of the Firefly Algorithm (FO) with the localized search and region-exploitation skills of the Spotted Hyena Optimization Algorithm (SHO). HFSHO aims to improve logistics path optimization and reduce operational costs. The algorithm’s effectiveness is systematically… More >

  • Open Access

    ARTICLE

    Analyzing the Impact of Blockchain Models for Securing Intelligent Logistics through Unified Computational Techniques

    Mohammed S. Alsaqer1, Majid H. Alsulami2,*, Rami N. Alkhawaji3, Abdulellah A. Alaboudi2

    CMC-Computers, Materials & Continua, Vol.77, No.3, pp. 3943-3968, 2023, DOI:10.32604/cmc.2023.042379 - 26 December 2023

    Abstract Blockchain technology has revolutionized conventional trade. The success of blockchain can be attributed to its distributed ledger characteristic, which secures every record inside the ledger using cryptography rules, making it more reliable, secure, and tamper-proof. This is evident by the significant impact that the use of this technology has had on people connected to digital spaces in the present-day context. Furthermore, it has been proven that blockchain technology is evolving from new perspectives and that it provides an effective mechanism for the intelligent transportation system infrastructure. To realize the full potential of the accurate and… More >

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