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  • Open Access

    ARTICLE

    A Multi-Objective Optimization for Locating Maintenance Stations and Operator Dispatching of Corrective Maintenance

    Chao-Lung Yang1,*, Melkamu Mengistnew Teshome1, Yu-Zhen Yeh1, Tamrat Yifter Meles2

    CMC-Computers, Materials & Continua, Vol.79, No.3, pp. 3519-3547, 2024, DOI:10.32604/cmc.2024.048462 - 20 June 2024

    Abstract In this study, we introduce a novel multi-objective optimization model tailored for modern manufacturing, aiming to mitigate the cost impacts of operational disruptions through optimized corrective maintenance. Central to our approach is the strategic placement of maintenance stations and the efficient allocation of personnel, addressing a crucial gap in the integration of maintenance personnel dispatching and station selection. Our model uniquely combines the spatial distribution of machinery with the expertise of operators to achieve a harmonious balance between maintenance efficiency and cost-effectiveness. The core of our methodology is the NSGA III+ Dispatch, an advanced adaptation… More >

  • Open Access

    ARTICLE

    A Strengthened Dominance Relation NSGA-III Algorithm Based on Differential Evolution to Solve Job Shop Scheduling Problem

    Liang Zeng1,2, Junyang Shi1, Yanyan Li1, Shanshan Wang1,2,*, Weigang Li3

    CMC-Computers, Materials & Continua, Vol.78, No.1, pp. 375-392, 2024, DOI:10.32604/cmc.2023.045803 - 30 January 2024

    Abstract The job shop scheduling problem is a classical combinatorial optimization challenge frequently encountered in manufacturing systems. It involves determining the optimal execution sequences for a set of jobs on various machines to maximize production efficiency and meet multiple objectives. The Non-dominated Sorting Genetic Algorithm III (NSGA-III) is an effective approach for solving the multi-objective job shop scheduling problem. Nevertheless, it has some limitations in solving scheduling problems, including inadequate global search capability, susceptibility to premature convergence, and challenges in balancing convergence and diversity. To enhance its performance, this paper introduces a strengthened dominance relation NSGA-III… More >

  • Open Access

    ARTICLE

    Dynamic Allocation of Manufacturing Tasks and Resources in Shared Manufacturing

    Caiyun Liu, Peng Liu*

    Intelligent Automation & Soft Computing, Vol.36, No.3, pp. 3221-3242, 2023, DOI:10.32604/iasc.2023.035114 - 15 March 2023

    Abstract Shared manufacturing is recognized as a new point-to-point manufacturing mode in the digital era. Shared manufacturing is referred to as a new manufacturing mode to realize the dynamic allocation of manufacturing tasks and resources. Compared with the traditional mode, shared manufacturing offers more abundant manufacturing resources and flexible configuration options. This paper proposes a model based on the description of the dynamic allocation of tasks and resources in the shared manufacturing environment, and the characteristics of shared manufacturing resource allocation. The execution of manufacturing tasks, in which candidate manufacturing resources enter or exit at various More >

  • Open Access

    ARTICLE

    An Optimization Capacity Design Method of Wind/Photovoltaic/Hydrogen Storage Power System Based on PSO-NSGA-II

    Lei Xing1, Yakui Liu2,3,*

    Energy Engineering, Vol.120, No.4, pp. 1023-1043, 2023, DOI:10.32604/ee.2023.025335 - 13 February 2023

    Abstract The optimal allocation of integrated energy system capacity based on the heuristic algorithms can reduce economic costs and achieve maximum consumption of renewable energy, which has attracted many attentions. However, the optimization results of heuristic algorithms are usually influenced by the choice of hyperparameters. To solve the above problem, the particle swarm algorithm is introduced to find the optimal hyperparameters of the heuristic algorithms. Firstly, an integrated energy system consisting of the photovoltaic, wind turbine, electrolysis cell, hydrogen storage tank, and energy storage is established. Meanwhile, the minimum economic cost, the maximum wind and PV… More >

  • Open Access

    ARTICLE

    Augmented Node Placement Model in -WSN Through Multiobjective Approach

    Kalaipriyan Thirugnansambandam1, Debnath Bhattacharyya2, Jaroslav Frnda3, Dinesh Kumar Anguraj2, Jan Nedoma4,*

    CMC-Computers, Materials & Continua, Vol.69, No.3, pp. 3629-3644, 2021, DOI:10.32604/cmc.2021.018939 - 24 August 2021

    Abstract In Wireless Sensor Network (WSN), coverage and connectivity are the vital challenges in the target-based region. The linear objective is to find the positions to cover the complete target nodes and connectivity between each sensor for data forwarding towards the base station given a grid with target points and a potential sensor placement position. In this paper, a multiobjective problem on target-based WSN (t-WSN) is derived, which minimizes the number of deployed nodes, and maximizes the cost of coverage and sensing range. An Evolutionary-based Non-Dominated Sorting Genetic Algorithm-II (NSGA-II) is incorporated to tackle this multiobjective problem… 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 - 01 January 2020

    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… More >

  • Open Access

    ARTICLE

    Optimization of Industrial Fluid Catalytic Cracking Unit having Five Lump Kinetic Scheme using Genetic Algorithm

    Shishir Sinha1, Praveen Ch.

    CMES-Computer Modeling in Engineering & Sciences, Vol.32, No.2, pp. 85-102, 2008, DOI:10.3970/cmes.2008.032.085

    Abstract Fluid catalytic cracking (FCC) unit plays most important role in the economy of a modern refinery that it is use for value addition to the refinery products. Because of the importance of FCC unit in refining, considerable effort has been done on the modeling of this unit for better understanding and improved productivity. The process is characterized by complex interactions among feed quality, catalyst properties, unit hardware parameters and process conditions. \newline The traditional and global approach of cracking kinetics is lumping. In the present paper, five lump kinetic scheme is considered, where gas oil… More >

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