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  • Open Access


    A Novel Collaborative Evolutionary Algorithm with Two-Population for Multi-Objective Flexible Job Shop Scheduling

    Cuiyu Wang, Xinyu Li, Yiping Gao*

    CMES-Computer Modeling in Engineering & Sciences, Vol.137, No.2, pp. 1849-1870, 2023, DOI:10.32604/cmes.2023.028098

    Abstract Job shop scheduling (JS) is an important technology for modern manufacturing. Flexible job shop scheduling (FJS) is critical in JS, and it has been widely employed in many industries, including aerospace and energy. FJS enables any machine from a certain set to handle an operation, and this is an NP-hard problem. Furthermore, due to the requirements in real-world cases, multi-objective FJS is increasingly widespread, thus increasing the challenge of solving the FJS problems. As a result, it is necessary to develop a novel method to address this challenge. To achieve this goal, a novel collaborative evolutionary algorithm with two-population based… More >

  • Open Access


    Competitive and Cooperative-Based Strength Pareto Evolutionary Algorithm for Green Distributed Heterogeneous Flow Shop Scheduling

    Kuihua Huang1, Rui Li2, Wenyin Gong2,*, Weiwei Bian3, Rui Wang1

    Intelligent Automation & Soft Computing, Vol.37, No.2, pp. 2077-2101, 2023, DOI:10.32604/iasc.2023.040215

    Abstract This work aims to resolve the distributed heterogeneous permutation flow shop scheduling problem (DHPFSP) with minimizing makespan and total energy consumption (TEC). To solve this NP-hard problem, this work proposed a competitive and cooperative-based strength Pareto evolutionary algorithm (CCSPEA) which contains the following features: 1) An initialization based on three heuristic rules is developed to generate a population with great diversity and convergence. 2) A comprehensive metric combining convergence and diversity metrics is used to better represent the heuristic information of a solution. 3) A competitive selection is designed which divides the population into a winner and a loser swarms… More >

  • Open Access


    Managing Software Testing Technical Debt Using Evolutionary Algorithms

    Muhammad Abid Jamil*, Mohamed K. Nour

    CMC-Computers, Materials & Continua, Vol.73, No.1, pp. 735-747, 2022, DOI:10.32604/cmc.2022.028386

    Abstract Technical debt (TD) happens when project teams carry out technical decisions in favor of a short-term goal(s) in their projects, whether deliberately or unknowingly. TD must be properly managed to guarantee that its negative implications do not outweigh its advantages. A lot of research has been conducted to show that TD has evolved into a common problem with considerable financial burden. Test technical debt is the technical debt aspect of testing (or test debt). Test debt is a relatively new concept that has piqued the curiosity of the software industry in recent years. In this article, we assume that the… 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


    Prediction of the Behavior of a Power System Using Root Cause Failure Analysis

    Seyed Mohammad Seyed Hosseini*, Kamran Shahanaghi, Safar Shasfand

    FDMP-Fluid Dynamics & Materials Processing, Vol.18, No.3, pp. 815-833, 2022, DOI:10.32604/fdmp.2022.019626


    The thermo-economic performance of a gas turbine is simulated using a fish bone technique to characterize the major equipment failure causes. Moreover a fault tree analysis and a Pareto technique are implemented to identify the related failure modes, and the percentage and frequency of failures, respectively. A pump 101 and drier 301 belonging to the Tabriz Petrochemical Company are considered for such analysis, which is complemented with a regression method to determine a behavioral model of this equipment over a twenty-year period. Research findings indicate that 81% of major failure factors in production equipment are related to the executive procedures… More >

  • Open Access


    FSpot: Fast and Efficient Video Encoding Workloads Over Amazon Spot Instances

    Anatoliy Zabrovskiy1,3, Prateek Agrawal1,2,*, Vladislav Kashansky1, Roland Kersche4, Christian Timmerer1,4, Radu Prodan1

    CMC-Computers, Materials & Continua, Vol.71, No.3, pp. 5677-5697, 2022, DOI:10.32604/cmc.2022.023630

    Abstract HTTP Adaptive Streaming (HAS) of video content is becoming an undivided part of the Internet and accounts for most of today's network traffic. Video compression technology plays a vital role in efficiently utilizing network channels, but encoding videos into multiple representations with selected encoding parameters is a significant challenge. However, video encoding is a computationally intensive and time-consuming operation that requires high-performance resources provided by on-premise infrastructures or public clouds. In turn, the public clouds, such as Amazon elastic compute cloud (EC2), provide hundreds of computing instances optimized for different purposes and clients’ budgets. Thus, there is a need for… More >

  • Open Access


    Multi-Objective High-Fidelity Optimization Using NSGA-III and MO-RPSOLC

    N. Ganesh1, Uvaraja Ragavendran2, Kanak Kalita3,*, Paras Jain4, Xiao-Zhi Gao5

    CMES-Computer Modeling in Engineering & Sciences, Vol.129, No.2, pp. 443-464, 2021, DOI:10.32604/cmes.2021.014960

    Abstract Optimizing the performance of composite structures is a real-world application with significant benefits. In this paper, a high-fidelity finite element method (FEM) is combined with the iterative improvement capability of metaheuristic optimization algorithms to obtain optimized composite plates. The FEM module comprises of ninenode isoparametric plate bending element in conjunction with the first-order shear deformation theory (FSDT). A recently proposed memetic version of particle swarm optimization called RPSOLC is modified in the current research to carry out multi-objective Pareto optimization. The performance of the MO-RPSOLC is found to be comparable with the NSGA-III. This work successfully highlights the use of… 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


    Ensemble Based Temporal Weighting and Pareto Ranking (ETP) Model for Effective Root Cause Analysis

    Naveen Kumar Seerangan1,*, S. Vijayaragavan Shanmugam2

    CMC-Computers, Materials & Continua, Vol.69, No.1, pp. 819-830, 2021, DOI:10.32604/cmc.2021.012135

    Abstract Root-cause identification plays a vital role in business decision making by providing effective future directions for the organizations. Aspect extraction and sentiment extraction plays a vital role in identifying the root-causes. This paper proposes the Ensemble based temporal weighting and pareto ranking (ETP) model for Root-cause identification. Aspect extraction is performed based on rules and is followed by opinion identification using the proposed boosted ensemble model. The obtained aspects are validated and ranked using the proposed aspect weighing scheme. Pareto-rule based aspect selection is performed as the final selection mechanism and the results are presented for business decision making. Experiments… More >

  • Open Access


    Inference on Generalized Inverse-Pareto Distribution under Complete and Censored Samples

    Abdelaziz Alsubie1, Mostafa Abdelhamid2, Abdul Hadi N. Ahmed2, Mohammed Alqawba3, Ahmed Z. Afify4,*

    Intelligent Automation & Soft Computing, Vol.29, No.1, pp. 213-232, 2021, DOI:10.32604/iasc.2021.018111

    Abstract In this paper, the estimation of the parameters of extended Marshall-Olkin inverse-Pareto (EMOIP) distribution is studied under complete and censored samples. Five classical methods of estimation are adopted to estimate the parameters of the EMOIP distribution from complete samples. These classical estimators include the percentiles estimators, maximum likelihood estimators, least squares estimators, maximum product spacing estimators, and weighted least-squares estimators. The likelihood estimators of the parameters under type-I and type-II censoring schemes are discussed. Simulation results were conducted, for various parameter combinations and different sample sizes, to compare the performance of the EMOIP estimation methods under complete and censored samples.… More >

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