As the strongly NP-hard problem, the hybrid flow-shop problem with multiprocessor tasks (HFSPMT) has gained increasing attention due to its academic significance and wide application background. For many heuristics an...
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As the strongly NP-hard problem, the hybrid flow-shop problem with multiprocessor tasks (HFSPMT) has gained increasing attention due to its academic significance and wide application background. For many heuristics and meta-heuristics to solve the HFSPMT, decoding method is the key element to decode sequences to schedules, which has great effect on the solution quality. To narrow the idle time between the consecutive operations in the processor and to increase the flexibility in selecting processors to schedule the following operations, several rules are proposed to adjust sequences to minimize the makespan of the HFSPMT. Based on the rules, a novel and effective decoding method named forward scheduling (FS) is proposed in this paper for solving the HFSPMT. At each stage, it first decodes the solution according to the non-decreasing order of the jobs' completion times at the previous stage, and then it adjusts the processing order of the jobs dynamically according to the rules to obtain potentially better schedule. Numerical results based on the well-known benchmarks and comparisons with some existing decoding methods demonstrate the effectiveness of the proposed FS decoding method.
The key for real-time collection of cutting tool information and its process tracking is to realize the encoding means and automatic identification of tool information. Therefore, the authors propose to encode tool in...
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ISBN:
(纸本)9780769538594
The key for real-time collection of cutting tool information and its process tracking is to realize the encoding means and automatic identification of tool information. Therefore, the authors propose to encode tool information in Data Matrix symbol and directly mark the symbol on tool surface. The tool information encoding scheme, the symbol image processing method and its error correction decoding algorithm, and the achievements' application in the cutting tool tracking process are all provided in this paper. The test results undertaken from a workshop environment show that the method can support the real-time information collection of cutting tool working process tracking, and greatly improve the management efficiency throughout the cutting tool life cycle.
We consider a decoding method for cyclic codes up to the Hartmann-Tzeng bound using the discrete Fourier transform. Indeed we propose how to make a submatrix or the circulant matrix from an error vector for this decod...
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ISBN:
(纸本)9781424413737
We consider a decoding method for cyclic codes up to the Hartmann-Tzeng bound using the discrete Fourier transform. Indeed we propose how to make a submatrix or the circulant matrix from an error vector for this decoding method. Moreover an example of a binary cyclic code, which could not be corrected by BCH decoding but be correctable by proposed decoding, is given. It is expected that this decoding method induces universal understanding for decoding method up to the Roos bound and the shift bound.
The digital fountain is a network encoding technology of an essentially infinite of encoded symbols,and LT codes is a class of codes that are useful in implementing an ideal digital *** on analysis of existing LT deco...
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ISBN:
(纸本)9781510805750
The digital fountain is a network encoding technology of an essentially infinite of encoded symbols,and LT codes is a class of codes that are useful in implementing an ideal digital *** on analysis of existing LT decoding algorithm,an improved method is *** each encoded symbol arrivals,the new method performs both the triangular and backsubstitution steps of Gaussian elimination on the fly,thus distributing the decoding work during all symbols reception and obtaining a short delay.
Transcranial acoustoelectric (AE) brain imaging (tABI) is a potential neuroimaging technique with high spatial (similar to mm) and temporal (similar to ms) resolution. decoding precision is critical for decoded signal...
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Transcranial acoustoelectric (AE) brain imaging (tABI) is a potential neuroimaging technique with high spatial (similar to mm) and temporal (similar to ms) resolution. decoding precision is critical for decoded signal quality and imaging performance. However, the traditional method is based on the fundamental component of the AE signal, overlooking the valuable information of its harmonics. Here, we present a signal decoding framework combining fundamental and harmonic components. Adopting filter bank analysis to efficiently integrate the fundamental and harmonic components, a weighted filter bank Hilbert transform (wFBHT) decoding method is implemented. With steady-state visual stimulation, both brain electric signal steady-state visual evoked potential (SSVEP) and AE signal of live rats were recorded using tABI. First, the signal-to-noise ratios (SNRs) characteristics of harmonic were analyzed. The decoded AE (decAE) signals of the second-sixth harmonic exhibited a highly consistent spectral response with SSVEP, which provided a theoretical basis for the framework. Then, using the grid search and nonlinear fitting, the impacts of harmonic number N and weight w on the change rate of correlation coefficient (CRCC) between the decAE signal and SSVEP were further explored. Results demonstrated that CRCC increased with harmonic number N significantly superior to the traditional method ( p = 0.0004 ). With equal weight of first-fourth harmonics, the highest correlation coefficient increased by 47%. What is more, the feasibility and performance were validated in live rats. Compared with that of the traditional method, the SNR of the decAE signal with wFBHT was 20.20 dB and increased by 72.1%.
The permutation flow shop scheduling problem (PFSP) is of wide application backgrounds and plays an important role in the manufacturing systems. With the serious energy concerns in manufacturing enterprises, peak powe...
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The permutation flow shop scheduling problem (PFSP) is of wide application backgrounds and plays an important role in the manufacturing systems. With the serious energy concerns in manufacturing enterprises, peak power consumption is considered one of the significant issues. For the PFSP with peak power consumption constraints (PFSPP), the real-time power consumption cannot exceed a given peak power at any time. Since the classical first-come first-serve scheduling method is not suitable for the PFSPP, this paper addresses the decoding methods to obtain feasible schedules based on the permutation encoding scheme. First, an earliest processing rule (EPR) is designed to determine the starting time of each operation, satisfying the power consumption constraints. Then, five decoding methods based on EPR are proposed to determine the suitable priority between the operations to yield feasible schedules with high quality. After analysing the complexity of the proposed decoding methods and comparing the performances via extensive numerical tests, some suggestions are provided for solving the PFSPP with different scales and power constraints.
In this article, an effective shuffled frog-leaping algorithm (SFLA) is proposed to solve the hybrid flow-shop scheduling problem with identical parallel machines (HFSP-IPM). First, some novel heuristic decoding rules...
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In this article, an effective shuffled frog-leaping algorithm (SFLA) is proposed to solve the hybrid flow-shop scheduling problem with identical parallel machines (HFSP-IPM). First, some novel heuristic decoding rules for both job order decision and machine assignment are proposed. Then, three hybrid decoding schemes are designed to decode job order sequences to schedules. A special bi-level crossover and multiple local search operators are incorporated in the searching framework of the SFLA to enrich the memetic searching behaviour and to balance the exploration and exploitation capabilities. Meanwhile, some theoretical analysis for the local search operators is provided for guiding the local search. The parameter setting of the algorithm is also investigated based on the Taguchi method of design of experiments. Finally, numerical testing based on well-known benchmarks and comparisons with some existing algorithms are carried out to demonstrate the effectiveness of the proposed algorithm.
In this article, an effective hybrid immune algorithm (HIA) is presented to solve the distributed permutation flow-shop scheduling problem (DPFSP). First, a decoding method is proposed to transfer a job permutation se...
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In this article, an effective hybrid immune algorithm (HIA) is presented to solve the distributed permutation flow-shop scheduling problem (DPFSP). First, a decoding method is proposed to transfer a job permutation sequence to a feasible schedule considering both factory dispatching and job sequencing. Secondly, a local search with four search operators is presented based on the characteristics of the problem. Thirdly, a special crossover operator is designed for the DPFSP, and mutation and vaccination operators are also applied within the framework of the HIA to perform an immune search. The influence of parameter setting on the HIA is investigated based on the Taguchi method of design of experiment. Extensive numerical testing results based on 420 small-sized instances and 720 large-sized instances are provided. The effectiveness of the HIA is demonstrated by comparison with some existing heuristic algorithms and the variable neighbourhood descent methods. New best known solutions are obtained by the HIA for 17 out of 420 small-sized instances and 585 out of 720 large-sized instances.
In this paper, a modified teaching-learning-based optimisation (mTLBO) algorithm is proposed to solve the re-entrant hybrid flowshop scheduling problem (RHFSP) with the makespan and the total tardiness criteria. Based...
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In this paper, a modified teaching-learning-based optimisation (mTLBO) algorithm is proposed to solve the re-entrant hybrid flowshop scheduling problem (RHFSP) with the makespan and the total tardiness criteria. Based on the simple job-based representation, a novel decoding method named equivalent due date-based permutation schedule is proposed to transfer an individual to a feasible schedule. At each generation, a number of superior individuals are selected as the teachers by the Pareto-based ranking phase. To enhance the exploitation ability in the promising area, the insertion-based local search is embedded in the search framework as the training phase for the TLBO. Due to the characteristics of the permutation-based discrete optimisation, the linear order crossover operator and the swap operator are adopted to imitate the interactions among the individuals in both the teaching phase and the learning phase. To store the non-dominated solutions explored during the search process, an external archive is used and updated when necessary. The influence of the parameter setting on the mTLBO in solving the RHFSP is investigated, and numerical tests with some benchmarking instances are carried out. The comparative results show that the proposed mTLBO outperforms the existing algorithms significantly.
The key innovation in Hadamard transform spectral imager (HTSI) introduced recently is the use of digital micro-mirror device (DMD) to encode spectral information. However, because the size of individual micro-mirrors...
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The key innovation in Hadamard transform spectral imager (HTSI) introduced recently is the use of digital micro-mirror device (DMD) to encode spectral information. However, because the size of individual micro-mirrors does not match the detector pixel size or for other unavoidable errors in the optical design and the system assembling, an interlaced encoding phenomenon appears on some pixels of the encoded images obtained from the detector. These interlaced encoding pixels are not encoded based on Hadamard transform, so they should be processed specially in spectrum recovery. This paper analyzes the interlaced encoding phenomenon and proposes a positioning method and a decoding method for the interlaced encoding pixels on the encoded images. In our experiment, we direct a beam of laser into our HTSI and fill the entire field of view: by observing the column vector, which is made up of the gray values of a pixel on the encoded images from the detector in sequence, the interlaced encoding pixels can be distinguished easily and a coefficient is obtained simultaneously, which denotes the ratio of the area between the left part and the right part of the interlaced encoding pixel. By substituting the coefficient and the encoded gray values of the interlaced pixel into its encoding equation, we can recover the spectral elements of the interlaced pixel with ease. By comparing the spectral curve of the interlaced encoding pixels recovered by the method mentioned in this paper and the spectral curves of its two adjacent pixels, we find the decoding results are quite effective. (C) 2011 Elsevier Ltd. All rights reserved.
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