At present, with the rapid development of the information industry, database technology has been greatly affected, and distributed database systems have gradually emerged. This article explains in detail the implement...
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This study considers an integrated process planning and scheduling (IPPS) problem for remanufacturing systems incorporating parallel disassembly workstations, a flexible job-shop-type reprocessing shop, and parallel r...
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This study considers an integrated process planning and scheduling (IPPS) problem for remanufacturing systems incorporating parallel disassembly workstations, a flexible job-shop-type reprocessing shop, and parallel reassembly workstations. This IPPS problem aims to determine the allocation/sequence of end-of-life products on the disassembly/reassembly shops and make decisions on the process path selection, operation sequencing, workstation allocation, and selection for reprocessing jobs. To solve the problem, a mixed-integer programming model is first built to characterize it mathematically, and a novel extended network graph is designed to represent and solve this problem visually. Then, an improved artificial bee colony algorithm is proposed that can solve the IPPS problem of remanufacturing systems with disassembly, reworking and reassembly shops simultaneously. In this introduced algorithm, a 3-level real-number solution representation scheme is adopted for encoding and decoding processes, and efficient neighborhood search structures are designed to improve the quality and diversity of the population. Computational experiments were systematically conducted on serval test instances. The results show that the proposed algorithm is highly advantageous for solving the IPPS problems in the remanufacturing systems by comparing it with four baseline algorithms.
This paper proposes a novel dynamic Petri net (PN) model based on Dempster-Shafer (D-S) evidence theory, and this improved evidential Petri net (EPN) model is used in knowledge inference and reliability analysis of co...
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This paper proposes a novel dynamic Petri net (PN) model based on Dempster-Shafer (D-S) evidence theory, and this improved evidential Petri net (EPN) model is used in knowledge inference and reliability analysis of complex mechanical systems. The EPN could take epistemic uncertainty such as interval information, subjective information into account by applying D-S evidence quantification theory. A dynamic representation model is also proposed based on the dynamic operation rules of the EPN model, and an improved artificial bee colony (abc) algorithm is employed to proceed optimization calculation during the complex systems' learning process. The improved abc algorithm and D-S evidence theory overcome the disadvantage of extremely subjective in traditional knowledge inference efficiently and thus could improve the accuracy of the EPN learning model. Through a simple numerical case and a satellite driving system analysis, this paper proves the superiority of the EPN and the dynamic knowledge representation method in reliability analysis of complex systems.
On the basis of a large number of documents, an improved artificial bee colony (abc) algorithm is proposed, and then is applied in the generalized electrical load modeling in this paper. Firstly, an update replacement...
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ISBN:
(纸本)9781467371063
On the basis of a large number of documents, an improved artificial bee colony (abc) algorithm is proposed, and then is applied in the generalized electrical load modeling in this paper. Firstly, an update replacement strategy of the worst nectars is presented by integrating the main principle of shuffled frog-leaping algorithm (SFLA) and abcalgorithm, in this way, the overall fitness of bee colonies is improved effectively, providing better optimizing performance as a result. Secondly, the structure of the generalized load model is given according to the impact of the distributed power to the load characteristic. The key problems such as the dynamic and static ratios, the difference between the rated and system capacities, and the initialization of motor are also analyzed in detail. Finally, the improvedabc is implied to the parameter identification of general.
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