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Suppressing residual vibration caused in objects carried by robots using a heuristic algorithm

PRECISION ENGINEERING-JOURNAL OF THE INTERNATIONAL SOCIETIES FOR PRECISION ENGINEERING AND NANOTECHNOLOGY 2023年 80卷 1-9页

作者： Ueno, Yusuke Tachiya, Hiroshi Komatsu Univ Fac Prod Syst Engn & Sci Komatsu Ishikawa 9238511 Japan Kanazawa Univ Adv Mobil Res Inst Kanazawa Ishikawa 9201192 Japan

When industrial robots transfer objects at high speeds, residual vibrations occur at the target positions. Recently, autonomous mobile robots such as AGV and AMR have become popular. However, the vibrations of the objects to be transported occur when the robot stops moving. Waiting until the residual vibration converges is necessary during the installation and assembly of transported objects. Thus, the overall work time increases even though the robots operate and move at a high speed. If the trajectory, which is the change in the position and attitude of the output point of a robot with time, can be adjusted such that the robot can move and operate within the same operation time by suppressing the residual vibration caused in transported objects, the work time can be significantly reduced. However, suppressing vibration is not easy because it usually requires solving complex equations of motion to consider the dynamics of robots. Therefore, in this study, based on the behavior of an object to be transported, which is measured by actually operating a robot, we propose a method for determining a trajectory that can suppress residual vibration using a heuristic algorithm without performing a kinetic analysis. The trajectories determined by this method reduced the settling time by approximately 90% with only a few dozen robot operations. The proposed method can be widely applied to commercial robots because appropriate trajectories are generated using a simple program that determines the variables used in the robot language without kinetic analysis.

关键词： Robot arm Residual vibration Trajectory planning heuristic algorithm Carried object

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GPU-Based Efficient Parallel heuristic algorithm for High-Utility Itemset Mining in Large Transaction Datasets

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IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING 2024年第2期36卷 652-667页

作者： Fang, Wei Jiang, Haipeng Lu, Hengyang Sun, Jun Wu, Xiaojun Lin, Jerry Chun-Wei Jiangnan Univ Dept Comp Sci & Technol Jiangsu Prov Engn Lab Pattern Recognit & Computat Wuxi 214122 Peoples R China Western Norway Univ Appl Sci Dept Comp Sci Elect Engn & Math Sci Bergen Norway

heuristic algorithms have been developed to find approximate solutions for high-utility itemset mining (HUIM) problems that compensate for the performance bottlenecks of exact algorithms. However, heuristic algorithms still face the problem of long runtime and insufficient mining quality, especially for large transaction datasets with thousands to tens of thousands of items and up to millions of transactions. To solve these problems, a novel GPU-based efficient parallel heuristic algorithm for HUIM (PHA-HUIM) is proposed in this paper. The iterative process of PHA-HUIM consists of three main steps: the search strategy, fitness evaluation, and ring topology communication. The search strategy and ring topology communication are designed to run in constant time on GPU. The parallelism of fitness evolution helps to substantially accelerate the algorithm. A new data structure with a sort-mapping strategy is proposed to enhance the search ability and reduce memory usage. To improve the mining quality, a multi-start strategy with an unbalanced allocation strategy is employed in the search process. Ring topology communication is adopted to maintain population diversity. A load balancing strategy is introduced to reduce the thread divergence to improve the parallel efficiency. The experimental results on nine large datasets show that PHA-HUIM outperforms state-of-the-art HUIM algorithms in terms of speedup performance, runtime, and mining quality.

关键词： High-utility itemset mining heuristic algorithm GPU parallel sort-mapping strategy load balancing

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A heuristic algorithm for Optimal Facility Placement in Mobile Edge Networks

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KSII TRANSACTIONS ON INTERNET AND INFORMATION SYSTEMS 2017年第7期11卷 3329-3350页

作者： Jiao, Jiping Chen, Lingyu Hong, Xuemin Shi, Jianghong Xiamen Univ Minist Educ Key Lab Underwater Acoust Commun & Marine Informa Xiamen 361005 Fujian Peoples R China

Installing caching and computing facilities in mobile edge networks is a promising solution to cope with the challenging capacity and delay requirements imposed on future mobile communication systems. The problem of optimal facility placement in mobile edge networks has not been fully studied in the literature. This is a non-trivial problem because the mobile edge network has a unidirectional topology, making existing solutions inapplicable. This paper considers the problem of optimal placement of a fixed number of facilities in a mobile edge network with an arbitrary tree topology and an arbitrary demand distribution. A low-complexity sequential algorithm is proposed and proved to be convergent and optimal in some cases. The complexity of the algorithm is shown to be O(H-2 gamma), where H is the height of the tree and gamma is the number of facilities. Simulation results confirm that the proposed algorithm is effective in producing near-optimal solutions.

关键词： Facility placement mobile edge network heuristic algorithm

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A heuristic algorithm for cell formation problems with consideration of multiple production factors

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INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY 2010年第9-12期46卷 1201-1213页

作者： Liu, ChenGuang Yin, Yong Yasuda, Kazuhiko Lian, Jie Tohoku Univ Math Inst Sendai Miyagi 9808578 Japan Xian Univ Technol Sch Management Xian 710048 Peoples R China Yamagata Univ Dept Econ & Business Management Yamagata 9908560 Japan Univ Texas Dallas Sch Management Richardson TX 75080 USA Tohoku Univ Grad Sch Econ & Management Sendai Miyagi 9808576 Japan

For the design of manufacturing cells, numerous mathematical models and various algorithms have been extensively investigated in the literature. However, most of the proposed models and algorithms have more or fewer drawbacks on the issues with real-life situations. In this paper, we propose a mathematical model that incorporates multiple key real-life production factors simultaneously, namely, production volume, batch size, alternative process routings and perfect coefficient of each routing, cell size, unit cost of intercell/intracell movements, and path coefficient of material flows. Then, to solve this NP-hard model, we develop a heuristic algorithm with three stages: (1) form the temporary machine group plan according to the alternative process routings of each part, (2) select the appropriate process routing of each part with respect to the over-all material movement cost, and (3) configure the regular manufacturing cells based on the appropriate process routing. A simple numerical example and an industrial case are used to test the computational performance of the proposed algorithm. The test results imply that it is useful for manufacturing cell design in both quality and speed.

关键词： Cellular manufacturing system Cell formation Multiple production factors heuristic algorithm

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Designing an optimal stope layout for underground mining based on a heuristic algorithm

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International Journal of Mining Science and Technology 2015年第5期25卷 767-772页

作者： Sandanayake Don Suneth Sameera Topal Erkan Asad Mohammad Waqar Ali Mining Engineering Western Australian School of MinesCurtin University

An optimal layout or three-dimensional spatial distribution of stopes guarantees the maximum profitability over life span of an underground mining ***,stope optimization is one of the key areas in underground mine planning ***,the computational complexity in developing an optimal stope layout has been a reason for limited availability of the algorithms offering solution to this *** article shares a new and efficient heuristic algorithm that considers a three-dimensional ore body model as an input,maximizes the economic value,and satisfies the physical mining and geotechnical constraints for generating an optimal stope *** implementation at a copper deposit demonstrates the applicability and robustness of the algorithm.A parallel processing based modification improving the performance of the original algorithm in terms of enormous computational time saving is also presented.

关键词： Stope optimization Underground mining Underground mine planning heuristic algorithm

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An efficient heuristic algorithm for arbitrary shaped rectilinear block packing problem

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COMPUTERS & OPERATIONS RESEARCH 2010年第6期37卷 1068-1074页

作者： Chen, Duanbing Liu, Jingfa Fu, Yan Shang, Mingsheng Univ Elect Sci & Technol China Sch Comp Sci Chengdu 610054 Peoples R China Nanjing Univ Informat Sci & Technol Sch Comp & Software Nanjing 210044 Peoples R China

Arbitrary shaped rectilinear block packing problem is a problem of packing a series of rectilinear blocks into a larger rectangular container, where arbitrary shaped rectilinear block is a polygonal block whose interior angle is either 90 degrees or 270 degrees. This problem involves many industrial applications, such as VLSI design, timber cutting, textile industry and layout of newspaper. Many algorithms based on different strategies have been presented to solve it. In this paper, we proposed an efficient heuristic algorithm which is based on principles of corner-occupying action and caving degree describing the quality of packing action. The proposed algorithm is tested on six instances from literatures and the results are rather satisfying. The computational results demonstrate that the proposed algorithm is rather efficient for solving the arbitrary shaped rectilinear block packing problem. (C) 2009 Elsevier Ltd. All rights reserved.

关键词： Rectilinear block packing heuristic algorithm Corner-occupying action Caving degree

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A fast and efficient heuristic algorithm for detecting community structures in complex networks

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PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS 2009年第13期388卷 2741-2749页

作者： Chen, Duanbing Fu, Yan Shang, Mingsheng Univ Elect Sci & Technol China Sch Comp Sci Chengdu 610054 Peoples R China

Community structure is an important property of complex networks. How to detect the communities is significant for understanding the network structure and to analyze the network properties. Many algorithms. such as K-L and GN, have been proposed to detect community structures in complex networks. According to daily experience, a community should have many nodes and connections. Based oil these principles and existing researches, a fast and efficient algorithm for detecting community structures in complex networks is proposed in this paper. The key strategy of the algorithm is to mine a node with the closest relations with the community and assign it to this community. Four real-world networks are used to test the performance of the algorithm. Experimental results demonstrate that the algorithm proposed is rather efficient for detecting community structures in complex networks. (C) 2009 Elsevier B.V. All rights reserved.

关键词： Complex networks heuristic algorithm Community structure Community size Connecting degree

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A new multi-objective approach in order to balancing and sequencing U-shaped mixed model assembly line problem: a proposed heuristic algorithm

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INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY 2015年第1-4期79卷 415-425页

作者： Manavizadeh, Neda Rabbani, Masoud Radmehr, Farzad KHATAM Inst Higher Educ Dept Ind Engn Tehran Iran Univ Tehran Dept Ind Engn Coll Engn Tehran Iran

Mixed model production is the practice of assembling different and distinct models in a line without change-overs responding to sudden demand changes for a variety of models. In this paper, to achieve a combination of balancing of the tasks and sequencing of models, both the balancing and sequencing problems are considered simultaneously. Three objective functions including: minimizing the cycle times, minimizing the wastages in each station, and minimizing the work overload by considering a multiple objective in both sequencing and balancing problem are investigated. One of the characteristics of this study is minimizing the wastages. The combination of those objectives in such problems has not been studied yet. Also, we propose a new heuristic algorithm and indicate that our results can be improved in the algorithm from the initial solution. Finally, the straight lines and U-lines in our problem are investigated;therefore, a decision maker can decide about the shape of assembly lines and compare the results in these cases.

关键词： Mixed model assembly lines Sequencing and balancing heuristic algorithm U-line Multi-objective

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A novel untapped flight segment flow prediction framework based on graph deep learning and heuristic algorithm for sustainable transport development

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JOURNAL OF THE OPERATIONAL RESEARCH SOCIETY 2024年

作者： Chen, Linlin Han, Shuihua Gupta, Shivam Sivarajah, Uthayasankar Yamoah, Fred A. Xiamen Univ Xiamen Peoples R China Neoma Business Sch Reims France Kingston Univ London Kingston Business Sch London England Buckinghamshire New Univ High Wycombe Campus Wycombe Buckinghamshire England

This study explores a novel machine learning framework for predicting the flow of untapped flight segments, focusing on the unique challenges posed by the absence of historical flow data in airline networks. Utilizing a real-world datasets from a major airline, we evaluate the performance of a graph deep learning-based approach that combines Multi-Graph Attention Networks (MGAT) and Long Short-Term Memory (LSTM) networks, as well as Nondominated Sorting Genetic algorithm II. The results demonstrate that the proposed framework significantly outperforms traditional models in accurately predicting passenger flow for new flight segments, particularly when compared to statistical benchmarks like time-series models that rely on historical flow data. Moreover, we find that optimizing the affinity coefficients within MGAT using the NSGA- II not only enhances predictive accuracy but also improves the interpretability of the model. Finally, we provide an in-depth analysis of the key factor that influence the predicted outcomes, highlighting the critical role of market competition in untapped segment operations.

关键词： Flow prediction heuristic algorithm multi-graph attention networks spatial-temporal dimension untapped flight segment

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A hybrid heuristic algorithm for the multistage supply chain network problem

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INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY 2005年第5-6期26卷 675-685页

作者： Yeh, WC Natl Chiayi Univ Dept Appl Math e Integrat & Collaborat Lab Taichung 408 Taiwan

In recent years, many developments in logistics were connected to the need for information in an efficient supply chain flow. The supply chain is often represented as a network called a supply chain network (SCN) that is comprised of nodes that represent facilities (suppliers, plants, distribution centers and customers). Arcs connect these nodes along with the production flow. A multistage SCN (MSCN) is a sequence of multiple SCN stages. The flow can only be transferred between two consecutive stages. The MSCN problem involves the choice of facilities (plants and distribution centers) to be opened and the distribution network design must satisfy the demand with minimum cost. In this paper, a revised mathematical model is first proposed to correct the fatal error appearing in the existing models. An efficient hybrid heuristic algorithm (HHA) was developed by combining a greedy method (GM), the linear programming technique (LP) and three local search methods (LSMs) (always used in solving the scheduling problem). The pair-wise exchange procedure (XP), the insert procedure (IP) and the remove procedure (RP) to solve the MSCN problem. Preliminary computational experiments demonstrate the efficiency and performance of the proposed HHA.

关键词： greedy method heuristic algorithm linear programming technique multistage supply chain network

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