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  • Open Access


    Multi-Objective Optimization of Energy Aware Virtual Machine Placement in Cloud Data Center

    B. Gomathi1, B. Saravana Balaji2, V. Krishna Kumar3, Mohamed Abouhawwash4,5,*, Sultan Aljahdali6, Mehedi Masud6, Nina Kuchuk7

    Intelligent Automation & Soft Computing, Vol.33, No.3, pp. 1771-1785, 2022, DOI:10.32604/iasc.2022.024052

    Abstract Cloud computing enables cloud providers to outsource their Information Technology (IT) services from data centers in a pay-as-you-go model. However, Cloud infrastructure comprises virtualized physical resources that consume huge amount of energy and emits carbon footprints to environment. Hence, there should be focus on optimal assignment of Virtual Machines (VM) to Physical Machines (PM) to ensure the energy efficiency and service level performance. In this paper, The Pareto based Multi-Objective Particle Swarm Optimization with Composite Mutation (PSOCM) technique has been proposed to improve the energy efficiency and minimize the Service Level Agreement (SLA) violation in Cloud Environment. In this paper,… More >

  • Open Access


    Crashworthiness Design and Multi-Objective Optimization for Bio-Inspired Hierarchical Thin-Walled Structures

    Shaoqiang Xu1, Weiwei Li1,*, Lin Li2, Tao Li1, Chicheng Ma1

    CMES-Computer Modeling in Engineering & Sciences, Vol.131, No.2, pp. 929-947, 2022, DOI:10.32604/cmes.2022.018964

    Abstract Thin-walled structures have been used in many fields due to their superior mechanical properties. In this paper, two types of hierarchical multi-cell tubes, inspired by the self-similarity of Pinus sylvestris, are proposed to enhance structural energy absorption performance. The finite element models of the hierarchical structures are established to validate the crashworthiness performance under axial dynamic load. The theoretical model of the mean crushing force is also derived based on the simplified super folded element theory. The finite element results demonstrate that the energy absorption characteristics and deformation mode of the bionic hierarchical thin-walled tubes are further improved with the… More >

  • Open Access


    Smart Anti-Pinch Window Simulation Using H-/H Criterion and MOPSO

    Maedeh Mohammadi Azni1, Mohammad Ali Sadrnia1, Shahab S. Band2,*, Zulkefli Bin Mansor3

    CMC-Computers, Materials & Continua, Vol.72, No.1, pp. 215-226, 2022, DOI:10.32604/cmc.2022.023030

    Abstract Automobile power windows are mechanisms that can be opened and shut with the press of a button. Although these windows can comfort the effort of occupancy to move the window, failure to recognize the person's body part at the right time will result in damage and in some cases, loss of that part. An anti-pinch mechanism is an excellent choice to solve this problem, which detects the obstacle in the glass path immediately and moves it down. In this paper, an optimal solution is presented for fault detection of the anti-pinch window system. The anti-pinch makes it possible to detect… More >

  • Open Access


    Weighted-adaptive Inertia Strategy for Multi-objective Scheduling in Multi-clouds

    Mazen Farid1,3,*, Rohaya Latip1,2, Masnida Hussin1, Nor Asilah Wati Abdul Hamid1

    CMC-Computers, Materials & Continua, Vol.72, No.1, pp. 1529-1560, 2022, DOI:10.32604/cmc.2022.021410

    Abstract One of the fundamental problems associated with scheduling workflows on virtual machines in a multi-cloud environment is how to find a near-optimum permutation. The workflow scheduling involves assigning independent computational jobs with conflicting objectives to a set of virtual machines. Most optimization methods for solving non-deterministic polynomial-time hardness (NP-hard) problems deploy multi-objective algorithms. As such, Pareto dominance is one of the most efficient criteria for determining the best solutions within the Pareto front. However, the main drawback of this method is that it requires a reasonably long time to provide an optimum solution. In this paper, a new multi-objective minimum… More >

  • Open Access


    Strengthened Initialization of Adaptive Cross-Generation Differential Evolution

    Wei Wan1, Gaige Wang1,2,3,*, Junyu Dong1

    CMES-Computer Modeling in Engineering & Sciences, Vol.130, No.3, pp. 1495-1516, 2022, DOI:10.32604/cmes.2021.017987

    Abstract Adaptive Cross-Generation Differential Evolution (ACGDE) is a recently-introduced algorithm for solving multiobjective problems with remarkable performance compared to other evolutionary algorithms (EAs). However, its convergence and diversity are not satisfactory compared with the latest algorithms. In order to adapt to the current environment, ACGDE requires improvements in many aspects, such as its initialization and mutant operator. In this paper, an enhanced version is proposed, namely SIACGDE. It incorporates a strengthened initialization strategy and optimized parameters in contrast to its predecessor. These improvements make the direction of crossgeneration mutation more clearly and the ability of searching more efficiently. The experiments show… More >

  • Open Access


    Deep Reinforcement Learning Model for Blood Bank Vehicle Routing Multi-Objective Optimization

    Meteb M. Altaf1,*, Ahmed Samir Roshdy2, Hatoon S. AlSagri3

    CMC-Computers, Materials & Continua, Vol.70, No.2, pp. 3955-3967, 2022, DOI:10.32604/cmc.2022.019448

    Abstract The overall healthcare system has been prioritized within development top lists worldwide. Since many national populations are aging, combined with the availability of sophisticated medical treatments, healthcare expenditures are rapidly growing. Blood banks are a major component of any healthcare system, which store and provide the blood products needed for organ transplants, emergency medical treatments, and routine surgeries. Timely delivery of blood products is vital, especially in emergency settings. Hence, blood delivery process parameters such as safety and speed have received attention in the literature, as well as other parameters such as delivery cost. In this paper, delivery time and… More >

  • Open Access


    Path Planning of Quadrotors in a Dynamic Environment Using a Multicriteria Multi-Verse Optimizer

    Raja Jarray1, Mujahed Al-Dhaifallah2,*, Hegazy Rezk3,4, Soufiene Bouallègue1,5

    CMC-Computers, Materials & Continua, Vol.69, No.2, pp. 2159-2180, 2021, DOI:10.32604/cmc.2021.018752

    Abstract Paths planning of Unmanned Aerial Vehicles (UAVs) in a dynamic environment is considered a challenging task in autonomous flight control design. In this work, an efficient method based on a Multi-Objective Multi-Verse Optimization (MOMVO) algorithm is proposed and successfully applied to solve the path planning problem of quadrotors with moving obstacles. Such a path planning task is formulated as a multicriteria optimization problem under operational constraints. The proposed MOMVO-based planning approach aims to lead the drone to traverse the shortest path from the starting point and the target without collision with moving obstacles. The vehicle moves to the next position… More >

  • Open Access


    An Optimized Framework for Surgical Team Selection

    Hemant Petwal*, Rinkle Rani

    CMC-Computers, Materials & Continua, Vol.69, No.2, pp. 2563-2582, 2021, DOI:10.32604/cmc.2021.017548

    Abstract In the healthcare system, a surgical team is a unit of experienced personnel who provide medical care to surgical patients during surgery. Selecting a surgical team is challenging for a multispecialty hospital as the performance of its members affects the efficiency and reliability of the hospital’s patient care. The effectiveness of a surgical team depends not only on its individual members but also on the coordination among them. In this paper, we addressed the challenges of surgical team selection faced by a multispecialty hospital and proposed a decision-making framework for selecting the optimal list of surgical teams for a given… More >

  • Open Access


    The Multi-Objective Optimization of AFPM Generators with Double-Sided Internal Stator Structures for Vertical Axis Wind Turbines

    Dandan Song1,*, Lianjun Zhou1, Ziqi Peng2, Senhua Luo2, Jun Zhu3

    Energy Engineering, Vol.118, No.5, pp. 1439-1452, 2021, DOI:10.32604/EE.2021.015011

    Abstract The axial flux permanent magnet (AFPM) generator with double-sided internal stator structure is highly suitable for vertical axis wind turbines due to its high power density. The performance of the AFPM generator with double-sided internal stator structure can be improved by the reasonable design of electromagnetic parameters. To further improve the overall performance of the AFPM generator with double-sided internal stator structure, multivariable (coil width ωc, permanent magnet thickness h, pole arc coefficient αp and working air gap lg) and multi-objective (generator efficiency η, total harmonic distortion of the voltage THD and induced electromotive force amplitude EMF) functional relationships are… More >

  • Open Access


    Optimal Allocation of Comprehensive Resources for Large-Scale Access of Electric Kiln to the Distribution Network

    Dan Wu1, Yanbo Che1, Wei Li2,*, Wei He3, Dongyi Li4

    Energy Engineering, Vol.118, No.5, pp. 1549-1564, 2021, DOI:10.32604/EE.2021.014818

    Abstract With the significant progress of the “coal to electricity” project, the electric kiln equipment began to be connected to the distribution network on a large scale, which caused power quality problems such as low voltage, high harmonic distortion rate, and high reactive power loss. This paper proposes a two-stage power grid comprehensive resource optimization configuration model. A multi-objective optimization solution based on the joint simulation platform of Matlab and OpenDSS is developed. The solution aims to control harmonics and optimize reactive power. In the first stage, a multi-objective optimization model is established to minimize the active network loss, voltage deviation,… More >

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