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  • Open Access

    ARTICLE

    An Adaptive Hybrid Metaheuristic for Solving the Vehicle Routing Problem with Time Windows under Uncertainty

    Manuel J. C. S. Reis*

    CMC-Computers, Materials & Continua, Vol.85, No.2, pp. 3023-3039, 2025, DOI:10.32604/cmc.2025.066390 - 23 September 2025

    Abstract The Vehicle Routing Problem with Time Windows (VRPTW) presents a significant challenge in combinatorial optimization, especially under real-world uncertainties such as variable travel times, service durations, and dynamic customer demands. These uncertainties make traditional deterministic models inadequate, often leading to suboptimal or infeasible solutions. To address these challenges, this work proposes an adaptive hybrid metaheuristic that integrates Genetic Algorithms (GA) with Local Search (LS), while incorporating stochastic uncertainty modeling through probabilistic travel times. The proposed algorithm dynamically adjusts parameters—such as mutation rate and local search probability—based on real-time search performance. This adaptivity enhances the algorithm’s… 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

    REVIEW

    Review of Internet of Things in Different Sectors: Recent Advances, Technologies, and Challenges

    Samreen Mahmood*

    Journal on Internet of Things, Vol.3, No.1, pp. 19-26, 2021, DOI:10.32604/jiot.2021.013071 - 16 March 2021

    Abstract Human beings and their activities are now connected through Internet of Things (IoT) with the evolution of wireless communication technologies. IoT is becoming popular and its usage is immensely increasing among various sectors. In this research paper, a comprehensive review has been conducted by considering recent and important literature review on IoT applications being operated in three major sectors. The three sectors studied are health, sports and transportation and logistics. Paper explored that with the help of IoT techniques, different miniature sized devices are invented which can record various parameters of human body, wearables devices More >

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