Chao-Lung Yang^1,*, 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 >

Liang Zeng^1,2, Junyang Shi¹, Yanyan Li¹, Shanshan Wang^1,2,*, 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 >

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 >

Lei Xing¹, Yakui Liu^2,3,*

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 >

Junfeng Zhao^{1, 2}, Weiming Feng¹, Jianping Yuan^{2, 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 >