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  • 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

    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

    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

    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

    Leveraging Blockchain with Optimal Deep Learning-Based Drug Supply Chain Management for Pharmaceutical Industries

    Shanthi Perumalsamy, Venkatesh Kaliyamurthy*

    CMC-Computers, Materials & Continua, Vol.77, No.2, pp. 2341-2357, 2023, DOI:10.32604/cmc.2023.040269

    Abstract Due to its complexity and involvement of numerous stakeholders, the pharmaceutical supply chain presents many challenges that companies must overcome to deliver necessary medications to patients efficiently. The pharmaceutical supply chain poses different challenging issues, encompasses supply chain visibility, cold-chain shipping, drug counterfeiting, and rising prescription drug prices, which can considerably surge out-of-pocket patient costs. Blockchain (BC) offers the technical base for such a scheme, as it could track legitimate drugs and avoid fake circulation. The designers presented the procedure of BC with fabric for creating a secured drug supply-chain management (DSCM) method. With this… More >

  • Open Access

    ARTICLE

    Delivery Service Management System Using Google Maps for SMEs in Emerging Countries

    Sophea Horng, Pisal Yenradee*

    CMC-Computers, Materials & Continua, Vol.75, No.3, pp. 6119-6143, 2023, DOI:10.32604/cmc.2023.038764

    Abstract This paper proposes a Delivery Service Management (DSM) system for Small and Medium Enterprises (SMEs) that own a delivery fleet of pickup trucks to manage Business-to-Business (B2B) delivery services. The proposed DSM system integrates four systems: Delivery Location Positioning (DLP), Delivery Route Planning (DRP), Arrival Time Prediction (ATP), and Communication and Data Sharing (CDS) systems. These systems are used to pinpoint the delivery locations of customers, plan the delivery route of each truck, predict arrival time (with an interval) at each delivery location, and communicate and share information among stakeholders, respectively. The DSM system deploys… More >

  • Open Access

    ARTICLE

    Scalable Blockchain Technology for Tracking the Provenance of the Agri-Food

    B. Subashini*, D. Hemavathi

    CMC-Computers, Materials & Continua, Vol.75, No.2, pp. 3339-3358, 2023, DOI:10.32604/cmc.2023.035074

    Abstract Due to an increase in agricultural mislabeling and carelesshandling of non-perishable foods in recent years, consumers have been calling for the food sector to be more transparent. Due to information dispersion between divisions and the propensity to record inaccurate data, current traceability solutions typically fail to provide reliable farm-to-fork histories ofproducts. The three most enticing characteristics of blockchain technology areopenness, integrity, and traceability, which make it a potentially crucial tool for guaranteeing the integrity and correctness of data. In this paper, we suggest a permissioned blockchain system run by organizations, such as regulatory bodies, to… More >

  • Open Access

    ARTICLE

    Bayes-Q-Learning Algorithm in Edge Computing for Waste Tracking

    D. Palanikkumar1, R. Ramesh Kumar2, Mehedi Masud3, Mrim M. Alnfiai4, Mohamed Abouhawwash5,6,*

    Intelligent Automation & Soft Computing, Vol.36, No.2, pp. 2425-2440, 2023, DOI:10.32604/iasc.2023.033879

    Abstract The major environmental hazard in this pandemic is the unhygienic disposal of medical waste. Medical wastage is not properly managed it will become a hazard to the environment and humans. Managing medical wastage is a major issue in the city, municipalities in the aspects of the environment, and logistics. An efficient supply chain with edge computing technology is used in managing medical waste. The supply chain operations include processing of waste collection, transportation, and disposal of waste. Many research works have been applied to improve the management of wastage. The main issues in the existing… More >

  • Open Access

    ARTICLE

    Application of Deep Learning to Production Forecasting in Intelligent Agricultural Product Supply Chain

    Xiao Ya Ma1,2,*, Jin Tong1,2, Fei Jiang3, Min Xu4, Li Mei Sun1, Qiu Yan Chen1

    CMC-Computers, Materials & Continua, Vol.74, No.3, pp. 6145-6159, 2023, DOI:10.32604/cmc.2023.034833

    Abstract Production prediction is an important factor influencing the realization of an intelligent agricultural supply chain. In an Internet of Things (IoT) environment, accurate yield prediction is one of the prerequisites for achieving an efficient response in an intelligent agricultural supply chain. As an example, this study applied a conventional prediction method and deep learning prediction model to predict the yield of a characteristic regional fruit (the Shatian pomelo) in a comparative study. The root means square error (RMSE) values of regression analysis, exponential smoothing, grey prediction, grey neural network, support vector regression (SVR), and long… More >

  • Open Access

    ARTICLE

    Multimodal Fuzzy Downstream Petroleum Supply Chain: A Novel Pentagonal Fuzzy Optimization

    Gul Freen1, Sajida Kousar1, Nasreen Kausar2, Dragan Pamucar3, Georgia Irina Oros4,*

    CMC-Computers, Materials & Continua, Vol.74, No.3, pp. 4861-4879, 2023, DOI:10.32604/cmc.2023.032985

    Abstract The petroleum industry has a complex, inflexible and challenging supply chain (SC) that impacts both the national economy as well as people’s daily lives with a range of services, including transportation, heating, electricity, lubricants, as well as chemicals and petrochemicals. In the petroleum industry, supply chain management presents several challenges, especially in the logistics sector, that are not found in other industries. In addition, logistical challenges contribute significantly to the cost of oil. Uncertainty regarding customer demand and supply significantly affects SC networks. Hence, SC flexibility can be maintained by addressing uncertainty. On the other… More >

  • Open Access

    ARTICLE

    Marketing Strategies Evaluation and Selection for Supply Chain Management Under Uncertainty

    Ngo Quang Trung, Nguyen Van Thanh*

    CMC-Computers, Materials & Continua, Vol.73, No.3, pp. 6535-6546, 2022, DOI:10.32604/cmc.2022.031815

    Abstract Sustainable marketing, often known as green marketing, has grown in popularity over the last two decades. Government is currently putting pressure to encourage firms to become environmentally aware in multiple aspects like human and financial utilization, advertisement, and product movement. Different types of companies are including many environmental campaigns into their own products to take advantage of the problem. Although many scholars have addressed the relevance of green marketing as well as theory development, this study is unique in that it examines both techniques in a fuzzy context. The integrated Fuzzy Multicriteria Decision Making Model More >

  • Open Access

    ARTICLE

    Bipolar Interval-Valued Neutrosophic Optimization Model of Integrated Healthcare System

    Sumbal Khalil1, Sajida Kousar1, Nasreen Kausar2, Muhammad Imran3, Georgia Irina Oros4,*

    CMC-Computers, Materials & Continua, Vol.73, No.3, pp. 6207-6224, 2022, DOI:10.32604/cmc.2022.030547

    Abstract Bipolar Interval-valued neutrosophic set is another generalization of fuzzy set, neutrosophic set, bipolar fuzzy set and bipolar neutrosophic set and thus when applied to the optimization problem handles uncertain data more efficiently and flexibly. Current work is an effort to design a flexible optimization model in the backdrop of interval-valued bipolar neutrosophic sets. Bipolar interval-valued neutrosophic membership grades are picked so that they indicate the restriction of the plausible infringement of the inequalities given in the problem. To prove the adequacy and effectiveness of the method a unified system of sustainable medical healthcare supply chain More >

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