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  • Open Access

    ARTICLE

    Efficient Network Selection Using Multi-Depot Routing Problem for Smart Cities

    R. Shanthakumari1, Yun-Cheol Nam2, Yunyoung Nam3,*, Mohamed Abouhawwash4,5

    Intelligent Automation & Soft Computing, Vol.36, No.2, pp. 1991-2005, 2023, DOI:10.32604/iasc.2023.033696

    Abstract Smart cities make use of a variety of smart technology to improve societies in better ways. Such intelligent technologies, on the other hand, pose significant concerns in terms of power usage and emission of carbons. The suggested study is focused on technological networks for big data-driven systems. With the support of software-defined technologies, a transportation-aided multicast routing system is suggested. By using public transportation as another communication platform in a smart city, network communication is enhanced. The primary objective is to use as little energy as possible while delivering as much data as possible. The Attribute Decision Making with Capacitated… More >

  • Open Access

    ARTICLE

    An Efficient Hybrid Algorithm for a Bi-objectives Hybrid Flow Shop Scheduling

    S. M. Mousavia, M. Zandiehb

    Intelligent Automation & Soft Computing, Vol.24, No.1, pp. 9-16, 2018, DOI:10.1080/10798587.2016.1261956

    Abstract This paper considers the problem of scheduling n independent jobs in g-stage hybrid flow shop environment. To address the realistic assumptions of the proposed problem, two additional traits were added to the scheduling problem. These include setup times, and the consideration of maximum completion time together with total tardiness as objective function. The problem is to determine a schedule that minimizes a convex combination of objectives. A procedure based on hybrid the simulated annealing; genetic algorithm and local search so-called HSA-GA-LS are proposed to handle this problem approximately. The performance of the proposed algorithm is compared with a genetic algorithm… More >

  • Open Access

    ARTICLE

    A Novel Two-Level Optimization Strategy for Multi-Debris Active Removal Mission in LEO

    Junfeng Zhao1, 2, Weiming Feng1, Jianping Yuan2, 3, *

    CMES-Computer Modeling in Engineering & Sciences, Vol.122, No.1, pp. 149-174, 2020, DOI:10.32604/cmes.2020.07504

    Abstract Recent studies of the space debris environment in Low Earth Orbit (LEO) have shown that the critical density of space debris has been reached in certain regions. The Active Debris Removal (ADR) mission, to mitigate the space debris density and stabilize the space debris environment, has been considered as a most effective method. In this paper, a novel two-level optimization strategy for multi-debris removal mission in LEO is proposed, which includes the low-level and high-level optimization process. To improve the overall performance of the multi-debris active removal mission and obtain multiple Pareto-optimal solutions, the ADR mission is seen as a… More >

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