A Multistate-Based Control System Approach Toward Optimal Maintenance Planning

Wang, Bo; Wu, Zhou; Xia, Xiaohua

doi:10.1109/tcst.2016.2550505

Cited by 24 publications

(16 citation statements)

References 27 publications

(44 reference statements)

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“…Yu et al studied a decomposition method for bound constrained optimization problems [15]. Stochastic algorithms such as evolutionary algorithms, particle swarm optimization [16,17], and artificial bee colony converge slower than deterministic ones [18][19][20] though they take objective functions as black-box, which makes these algorithms applicable to nearly all kinds of antenna design problems. Parallel execution of optimization algorithms could greatly save computational time [21,22].…”

Section: Introductionmentioning

confidence: 99%

Tuning rectangular microstrip antenna through scan and zoom algorithm

Zhang

2018

J Wireless Com Network

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Microstrip antennas have been widely studied and can be applied to a large number of wide frequency domain in wireless communication. Microstrip antennas are featured with light weight, small volume, and low cost advantages. Planar or spatial structures could substantially affect the frequency reliability and sidelobe level of microstrip antennas. Designing high performance microstrip antennas requires the tuning of the length and width of microstrip patch, the equivalent permittivity, the feed position of the coaxial line, and so on. Although electromagnetic theory could provide a solution for antenna design, such solution is probably not optimal solution due to complex environment and the affection of multiple factors. This paper attempts to tuning the design of microstrip antennas by using scan and zoom algorithm. It does not require derivative information of antenna model. This algorithm consists of search space scan and search domain zoom stages. The effectiveness of the scan and zoom algorithm is firstly tested on mathematical functions. The algorithm is then verified on rectangular microstrip antenna design. Compared with theoretical solution, the novel algorithm attains better design solution. The algorithm can also be easily extended to tackle other antenna design problems.

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Section: Introductionmentioning

confidence: 99%

Tuning rectangular microstrip antenna through scan and zoom algorithm

Zhang

2018

J Wireless Com Network

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“…One major research focus for the building retrofitting is the retrofitting planning [2][3][4]. In addition, studies also reveal that the maintenance of retrofitted items makes significant contributions to the final performance of a building energy retrofitting project, due to the negative impact from item malfunctions and deterioration [5][6][7].…”

Section: Introductionmentioning

confidence: 99%

“…Wang et al [7] further take into account the performance deterioration and failures simultaneously in the preceding maintenance plan optimization problem. A multistate system approach is employed, where retrofitted items are considered to have multiple working states and a failure state [11,12].…”

Section: Introductionmentioning

confidence: 99%

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A Multiscale Differential Evolution Algorithm‐Based Maintenance Plan Optimization for Building Energy Retrofitting

Wang

Liu

2018

Complexity

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This paper addresses a maintenance plan optimization problem for building energy retrofitting with a novel differential evolution-based algorithm. The problem manifests substantial complexity due to the parallel optimization of the maintenance time scale, maintenance instants, and maintenance rates, with multiple objectives and time scales. The problem is formulated based on an impulsive and switched phenomenon, with objectives of maximizing the energy performances and economic indicators for the retrofitting project over a finite horizon. A multiscale differential evolution algorithm is accordingly proposed to be the numerical solver. The proposed algorithm is able to optimize the decision variables simultaneously, especially the maintenance time scale that can influence the number of other decision variables. Simulation results illustrate the effectiveness of the proposed approach.

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“…Besides GA, other evolutionary algorithms have been applied in real-world problems [16][17][18][19]. Min et al considered pulse compression and sidelobe suppression in [20].…”

Section: Introductionmentioning

confidence: 99%

Nonuniform antenna array design by parallelizing three-parent crossover genetic algorithm

Zhang

2017

J Wireless Com Network

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Antenna plays a very important role in wireless communication. Array elements laid out nonuniformly could achieve better frequency reliability and lower sidelobe level than uniform spaced elements. Designing desirable nonuniform antenna array requires the tuning of distances between each element, excitation, amplitude, and so on. Such design problem can be solved by genetic algorithm. Based on a recently genetic algorithm modification, this paper attempts to invent a parallel framework to enhance the efficiency of genetic algorithm. The parallel framework increases exploitation search of genetic algorithm. The effectiveness of the proposed algorithm is firstly demonstrated on toy problems with different kinds of problem complexity. The proposed algorithm is then verified on nonuniform antenna array design. Compared with genetic algorithm without parallelization, the novel algorithm attains better design solution and saves a lot computation time.

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A Multistate-Based Control System Approach Toward Optimal Maintenance Planning

Cited by 24 publications

References 27 publications

Tuning rectangular microstrip antenna through scan and zoom algorithm

Tuning rectangular microstrip antenna through scan and zoom algorithm

A Multiscale Differential Evolution Algorithm‐Based Maintenance Plan Optimization for Building Energy Retrofitting

Nonuniform antenna array design by parallelizing three-parent crossover genetic algorithm

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