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Improved method for the feature extraction of laser scanner using genetic clustering

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Journal of Systems Engineering and Electronics 2008年第2期19卷 280-285页

作者： Yu Jinxia Cai Zixing Duan Zhuohua Coll. of Information ScienCe and Engineering Central South Univ. Changsha 410083 P. R. China Coll. of Computer Science and Technology Henan Polytechnic Univ. Jiaozuo 454003 P. R. China Dept. of Computer Science Shaoguan Univ. Shaoguan 512003 P. R. China

Feature extraction of range images provided by ranging sensor is a key issue of pattern recognition. To automatically extract the environmental feature sensed by a 2D ranging sensor laser scanner, an improved method based on genetic clustering VGA-clustering is presented. By integrating the spatial neighbouring information of range data into fuzzy clustering algorithm. a weighted fuzzy clustering algorithm.（WFCA） instead of standard clustering algorithm.is introduced to realize feature extraction of laser scanner. Aimed at the unknown clustering number in advance, several validation index functions are used to estimate the validity of different clustering algorithm. and one validation index is selected as the fitness function of genetic algorithm.so as to determine the accurate clustering number automatically. At the same time, an improved genetic algorithm.IVGA on the basis of VGA is proposed to solve the local optimum of clustering algorithm. which is implemented by increasing the population diversity and improving the genetic operators of elitist rule to enhance the local search capacity and to quicken the convergence speed. By the comparison with other algorithm., the effectiveness of the algorithm.introduced is demonstrated.

关键词： laser scanner feature extraction weighted fuzzy clustering validation index genetic algorithm.

Using genetic/simulated annealing algorithm.to solve disassembly sequence planning

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Journal of Systems Engineering and Electronics 2009年第4期20卷 906-912页

作者： Wu Hao Zuo Hongfu Coll. of Civil Aviation Nanjing Univ. of Aeronautics and Astronautics Nanjing 210016 P. R. China

Disassembly sequence planning （DSP） plays a significant role in maintenance planning of the aircraft. It is used during the design stage for the analysis of maintainability of the aircraft. To solve product disassembly sequence planning problems efficiently, a product disassembly hybrid graph model, which describes the connection, non-connection and precedence relationships between the product parts, is established based on the characteristic of disassembly. Farther, the optimization model is provided to optimize disassembly sequence. And the solution methodology based on the genetic/simulated annealing algorithm.with binaxy-tree algorithm.is given. Finally, an example is analyzed in detail, and the result shows that the model is correct and efficient.

关键词： disassembly sequence planning disassembly hybrid graph connection matrix precedence matrix binary-tree algorithm. simulated annealing algorithm genetic algorithm.

genetic algorithm.for λ-optimal translation sequence of rough communication

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Journal of Systems Engineering and Electronics 2011年第4期22卷 609-614页

作者： Hongkai Wang Yanyong Guan Chunhua Yuan School of Mathematics University of Jinan Jinan 250022 R R. China

In rough communication, because each agent has a different language and can not provide precise communication to each other, the concept translated among multi-agents will loss some information, and this results in a less or rougher concept. With different translation sequences the amount of the missed knowledge is varied. The λ-optimal translation sequence of rough communication, which concerns both every agent and the last agent taking part in rough communication to get information as much as he （or she） can, is given. In order to get the λ-optimal translation sequence, a genetic algorithm.is used. Analysis and simulation of the algorithm.demonstrate the effectiveness of the approach.

关键词： rough sets rough communication λ-optimal trans-lation sequence genetic algorithm.

Node ordinal encoded genetic algorithm.for the optimal allocation of water resources

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Progress in Natural Science:Materials International 2005年第5期15卷 448-452页

作者： YANG Xiaohua1*, YANG Zhifeng 1,2, SHEN Zhenyao1 and LI Jianqiang3(1. State Key Laboratory of Water Environment Simulation, School of Environment, Beijing Normal University, Beijing 100875, China 2. Key Laboratory for Water and Sediment Sciences Ministry of Education, School of Environment, Beijing Normal University, Beijing 100875, China 3. Water Resources and Hydropower Planning and Design General Institute, MWR, Beijing 100011, China) State Key Lab. of Water Environ. Simulation Sch. of Environ. Beijing Normal Univ. Beijing 100875 China Key Lab. for Water and Sediment Sci. Min. of Edu. Sch. of Environ. Beijing Normal Univ. Beijing 100875 China Water Resources and Hydropower Planning and Design General Inst. MWR Beijing 100011 China

A new method, node ordinal encoded genetic algorithm.(NOEGA), is proposed for solving water resources optimal allocation problems, in which the capacity of water resources is split into a number of smaller parts so that successive operations can be overlapped. Our objective is to maximize the whole benefit function. To overcome the “dimensionality and algorithm.complexity curse” while searching for solutions and looking for an optimal solution, the operations of one-point crossover operator, gene exchange operator, gene random operator, gene shift operator and node ordinal strings are established. It is proved to be an effective optimal method in searching for global solutions. The NOEGA does not need a diversity of initial population, and it does not have the problem of immature convergence. The results of two cases show that using NOEGA to solve the optimal allocation model is very efficient and robust. In addition, the algorithm.complexity of NOEGA is discussed.

关键词： water resources optimal allocation node ordinal code genetic algorithm.

genetic algorithm.based wide-band deterministic maximum likelihood direction finding algorithm

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Journal of Systems Engineering and Electronics 2005年第3期16卷 510-514页

作者：李福昌赵春晖 Coll .of Information &Communication Engineering Harbin Engineering Univ

The wide-band direction finding is one of hit and difficult task in array signal processing. This paper generalizes narrow-band deterministic maximum likelihood direction finding algorithm.to the wideband case, and so constructions an object function, then utilizes genetic algorithm.for nonlinear global optimization. Direction of arrival is estimated without preprocessing of array data and so the algorithm.eliminates the effect of pre-estimate on the final estimation. The algorithm.is applied on uniform linear array and extensive simulation results prove the efficacy of the algorithm. In the process of simulation, we obtain the relation between estimation error and parameters of genetic algorithm.

关键词： wide-band direction finding deterministic maximum likelihood genetic algorithm.

2-D mini mumfuzzy entropy method of image thresholding based on genetic algorithm

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Journal of Systems Engineering and Electronics 2005年第3期16卷 557-560页

作者：张兴会刘玲 Tianjin Univ .of Technology and Education

A new image thresholding method is introduced, which is based on 2-D histgram and minimizing the measures of fuzziness of an input image. A new definition of fuzzy membership function is proposed, it denotes the characteristic relationship between the gray level of each pixel and the average value of its neighborhood. When the threshold is not located at the obvious and deep valley of the histgram, genetic algorithm.is devoted to the problem of selecting the appropriate threshold value. The experimental results indicate that the proposed method has good performance.

关键词： image thresholding 2-D fuzzy entropy genetic algorithm.

Robust Assignment of Airport Gates with Operational Safety Constraints

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International Journal of Automation and computing 2016年第1期13卷 31-41页

作者： Shuo Liu Wen-Hua Chen Jiyin Liu Department of Aeronautical and Automotive Engineering Loughborough University School of Business and Economics Loughborough University

This paper reviews existing approaches to the airport gate assignment problem （AGAP） and presents an optimization model for the problem considering operational safety constraints. The main objective is to minimize the dispersion of gate idle time periods （to get robust optimization） while ensuring appropriate matching between the size of each aircraft and its assigned gate type and avoiding the potential hazard caused by gate apron operational conflict. genetic algorithm.is adopted to solve the problem, An illustrative example is given to show the effectiveness and efficiency of the algorithm. The algorithm.performance is further demonstrated using data of a terminal from Beijing Capital International Airport （PEK）.

关键词： Gate assignment problem operational safety constraints robust optimization conflict avoidance genetic algorithm.

Human resources allocation for aircraft maintenance with predefined sequence

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Journal of Systems Engineering and Electronics 2010年第6期21卷 1008-1013页

作者： Zhaodong Huang Wenbing Chang Yiyong Xiao Yuchun Xu Rui Liu School of Reliability and Systems Engineering Beihang University Beijing 100191 E R. China School of Applied Sciences Cranfield University Cranfield MK43 0AL UK

There are always large-scale items in the maintenances schedule of aircraft system, many of which have been fixed to be done in predefined sequences, which leads the workflow to be sys-tematically complex and makes this kind of problem quite different from all sorts of existing job-selection modes. On the other hand, the human resources are always limited and men have different working capabilities on different items, which make the allocation operation of human resources be much roomy. However, the final total time span of maintenance is often required to be as short as possible in many practices, in order to suffer only the lowest cost of loss while the system is stopping. A new model for op-timizing the allocation if aircraft maintenance human resources with the constraint of predefined sequence is presented. The ge-netic algorithm.is employed to find the optimal solution that holds the shortest total time span of maintenance. To generate the ul-timate maintenance work items and the human resource array, the sequences among all maintenance work items are considered firstly, the work item array is then generated through traversal with the constraint of maintenance sequence matrix, and the human resources are finally allocated according to the work item array with the constraint of the maintenance capability. An example is demonstrated to show that the model and algorithm.behave a satisfying performance on finding the optimal solution as expected.

关键词： aircraft maintenance human resources allocation predefined sequence genetic algorithm.

Location and allocation problem for spare parts depots on integrated logistics support

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Journal of Systems Engineering and Electronics 2019年第6期30卷 1252-1259页

作者： WEN Meilin LU Bohan LI Shuyu KANG Rui School of Reliability and Systems Engineering Beihang UniversityBeijing 100191China Science and Technology on Reliability and Environmental Engineering Laboratory Beijing 100191China

In equipment integrated logistics support(ILS), the supply capability of spare parts is a significant factor. There are lots of depots in the traditional support system, which makes too many redundant spare parts and causes high cost of support. Meanwhile,the inconsistency among depots makes it difficult to manage spare parts. With the development of information technology and transportation, the supply network has become more efficient. In order to further improve the efficiency of supply-support work and the availability of the equipment system, building a system of one centralized depot with multiple depots becomes an appropriate way.In this case, location selection of the depots including centralized depots and multiple depots becomes a top priority in the support system. This paper will focus on the location selection problem of centralized depots considering ILS factors. Unlike the common location selection problem, depots in ILS require a higher service level. Therefore, it becomes desperately necessary to take the high requirement of the mission into account while determining location of depots. Based on this, we raise an optimal depot location model. First, the expected transportation cost is calculated.Next, factors in ILS such as response time, availability and fill rate are analyzed for evaluating positions of open depots. Then, an optimization model of depot location is developed with the minimum expected cost of transportation as objective and ILS factors as constraints. Finally, a numerical case is studied to prove the validity of the model by using the genetic algorithm. Results show that depot location obtained by this model can guarantee the effectiveness and capability of ILS well.

关键词： location problem spare parts depot integrated logis tics support genetic algorithm.