Home / Advanced Search

  • Title/Keywords

  • Author/Affliations

  • Journal

  • Article Type

  • Start Year

  • End Year

Update SearchingClear
  • Articles
  • Online
Search Results (8)
  • Open Access

    ARTICLE

    An Enhanced Adaptive Differential Evolution Approach for Constrained Optimization Problems

    Wenchao Yi, Zhilei Lin, Yong Chen, Zhi Pei*, Jiansha Lu

    CMES-Computer Modeling in Engineering & Sciences, Vol.136, No.3, pp. 2841-2860, 2023, DOI:10.32604/cmes.2023.027055

    Abstract Effective constrained optimization algorithms have been proposed for engineering problems recently. It is common to consider constraint violation and optimization algorithm as two separate parts. In this study, a pbest selection mechanism is proposed to integrate the current mutation strategy in constrained optimization problems. Based on the improved pbest selection method, an adaptive differential evolution approach is proposed, which helps the population jump out of the infeasible region. If all the individuals are infeasible, the top 5% of infeasible individuals are selected. In addition, a modified truncated ε-level method is proposed to avoid trapping in infeasible regions. The proposed adaptive… More > Graphic Abstract

    An Enhanced Adaptive Differential Evolution Approach for Constrained Optimization Problems

  • Open Access

    ARTICLE

    Modified Differential Evolution Algorithm for Solving Dynamic Optimization with Existence of Infeasible Environments

    Mohamed A. Meselhi*, Saber M. Elsayed, Daryl L. Essam, Ruhul A. Sarker

    CMC-Computers, Materials & Continua, Vol.74, No.1, pp. 1-17, 2023, DOI:10.32604/cmc.2023.027448

    Abstract Dynamic constrained optimization is a challenging research topic in which the objective function and/or constraints change over time. In such problems, it is commonly assumed that all problem instances are feasible. In reality some instances can be infeasible due to various practical issues, such as a sudden change in resource requirements or a big change in the availability of resources. Decision-makers have to determine whether a particular instance is feasible or not, as infeasible instances cannot be solved as there are no solutions to implement. In this case, locating the nearest feasible solution would be valuable information for the decision-makers.… More >

  • Open Access

    ARTICLE

    Optimization of Heat Treatment Scheduling for Hot Press Forging Using Data-Driven Models

    Seyoung Kim1, Jeonghoon Choi1, Kwang Ryel Ryu2,*

    Intelligent Automation & Soft Computing, Vol.32, No.1, pp. 207-220, 2022, DOI:10.32604/iasc.2022.021752

    Abstract Scheduling heat treatment jobs in a hot press forging factory involves forming batches of multiple workpieces for the given furnaces, determining the start time of heating each batch, and sorting out the order of cooling the heated workpieces. Among these, forming batches is particularly difficult because of the various constraints that must be satisfied. This paper proposes an optimization method based on an evolutionary algorithm to search for a heat treatment schedule of maximum productivity with minimum energy cost, satisfying various constraints imposed on the batches. Our method encodes a candidate solution as a permutation of heat treatment jobs and… More >

  • Open Access

    ARTICLE

    Rock Hyraxes Swarm Optimization: A New Nature-Inspired Metaheuristic Optimization Algorithm

    Belal Al-Khateeb1,*, Kawther Ahmed2, Maha Mahmood1, Dac-Nhuong Le3,4

    CMC-Computers, Materials & Continua, Vol.68, No.1, pp. 643-654, 2021, DOI:10.32604/cmc.2021.013648

    Abstract This paper presents a novel metaheuristic algorithm called Rock Hyraxes Swarm Optimization (RHSO) inspired by the behavior of rock hyraxes swarms in nature. The RHSO algorithm mimics the collective behavior of Rock Hyraxes to find their eating and their special way of looking at this food. Rock hyraxes live in colonies or groups where a dominant male watch over the colony carefully to ensure their safety leads the group. Forty-eight (22 unimodal and 26 multimodal) test functions commonly used in the optimization area are used as a testing benchmark for the RHSO algorithm. A comparative efficiency analysis also checks RHSO… More >

  • Open Access

    ARTICLE

    A Geometrical Approach to Compute Upper Limb Joint Stiffness

    Davide Piovesan1, *, Roberto Bortoletto2

    CMES-Computer Modeling in Engineering & Sciences, Vol.123, No.1, pp. 23-47, 2020, DOI:10.32604/cmes.2020.09231

    Abstract Exoskeletons are designed to control the forces exerted during the physical coupling between the human and the machine. Since the human is an active system, the control of an exoskeleton requires coordinated action between the machine and the load so to obtain a reciprocal adaptation. Humans in the control loop can be modeled as active mechanical loads whose stiffness is continuously changing. The direct measurement of human stiffness is difficult to obtain in real-time, thus posing a significant limitation to the design of wearable robotics controllers. Electromyographic (EMG) recordings can provide an indirect estimation of human muscle force and stiffness,… More >

  • Open Access

    ARTICLE

    Chance-Constrained Optimization of Pumping in Coastal Aquifers by Stochastic Boundary Element Method and Genetic Algorithm

    B. Amaziane1, A. Naji2, D. Ouazar3, A. H.-D. Cheng4

    CMC-Computers, Materials & Continua, Vol.2, No.2, pp. 85-96, 2005, DOI:10.3970/cmc.2005.002.085

    Abstract In this paper the optimization of groundwater pumping in coastal aquifers under the threat of saltwater intrusion is investigated. The aquifer is inhomogeneous and contains several hydraulic conductivities zones. The aquifer data such as the hydraulic conductivities are uncertain, but with their expected mean and standard deviation values given. A stochastic boundary element method based on the perturbation technique is employed as the simulation tool. The stochastic optimization is handled by the chance-constrained programming. Genetic algorithm is selected as the optimization tool. Numerical examples of deterministic and stochastic problems are provided to demonstrate the feasibility of the proposed schemes. More >

  • Open Access

    ARTICLE

    Constrained Optimization Multi-dimensional Harmonic Balance Method for Quasi-periodic Motions of Nonlinear Systems

    Haitao Liao1

    CMES-Computer Modeling in Engineering & Sciences, Vol.95, No.3, pp. 207-234, 2013, DOI:10.3970/cmes.2013.095.207

    Abstract The constrained optimization multi-dimensional harmonic balance method for calculating the quasi-periodic solutions of nonlinear systems is presented. The problem of determining the worst quasi-periodic response is transformed into a nonlinear optimization problem with nonlinear equality constraints. The general nonlinear equality constraints are built using a set of nonlinear algebraic equations which is derived using the multi-dimensional harmonic balance method. The Multi- Start algorithm is adopted to solve the resulting constrained maximization problem. Finally, the validity of the proposed method is demonstrated with a Duffing oscillator and numerical case studies for problems with uncertainties are performed on a nonlinear two-degree of… More >

  • Open Access

    ARTICLE

    Inverse Scatterer Reconstruction in a Halfplane Using Surficial SH Line Sources

    C. Jeong1, L.F. Kallivokas2

    CMES-Computer Modeling in Engineering & Sciences, Vol.35, No.1, pp. 49-72, 2008, DOI:10.3970/cmes.2008.035.049

    Abstract We discuss the inverse scattering problem of identifying the shape and location of a rigid scatterer fully buried in a homogeneous halfplane, when illuminated by surficial (line) wave sources generating SH waves. To this end, we consider the full-waveform response of the coupled host-obstacle system in the frequency domain, and employ the apparatus of partial-differential-equation-constrained optimization, augmented with total differentiation for tracking shape evolutions across inversion iterations, and specialized continuation schemes in lieu of formal regularization. We report numerical results that provide evidence of algorithmic robustness for detecting a variety of shapes, including elliptically- and kite-shaped obstacles. More >

Displaying 1-10 on page 1 of 8. Per Page