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Geometric Optimization of a Delta Type Parallel Robot Using harmony search algorithm

ROBOTICA 2019年第9期37卷 1494-1512页

作者： Mazare, Mahmood Taghizadeh, Mostafa Shahid Beheshti Univ Sch Mech Engn Tehran Iran

This paper aims to provide an optimal design of geometric parameters of a special architecture of the delta parallel mechanism, in order to improve positioning accuracy, workspace size, and kinematic and dynamic performance characteristics. In the studied 3[P2(US)] robot, the radius of both fixed and moving platforms, length of the connecting rods, and installation angle of the actuators of the manipulator are chosen as the decision variables. These parameters are optimized to maximize the weighted objective function, comprising workspace volume, global dexterity, global mass, global error, and global error sensitivity indices. Optimizations are performed employing two distinct algorithms, Genetic and harmony search whose results confirm each other. The optimal design of the robot leads to maximum workspace size, high dexterity, and dynamic performance, with a minimum error of the end-effector position in its reachable workspace.

关键词： Parallel robot Optimization harmony search algorithm Accuracy Performance indices

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Nurse Scheduling with Opposition-Based Parallel harmony search algorithm

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JOURNAL OF INTELLIGENT SYSTEMS 2019年第4期28卷 633-647页

作者： Yagmur, Ece Cetin Sarucan, Ahmet Selcuk Univ Fac Engn Dept Ind Engn TR-42050 Konya Turkey

One of the advances made in the management of human resources for the effective implementation of service delivery is the creation of personnel schedules. In this context, especially in terms of the majority of health-care systems, creating nurse schedules comes to the fore. Nurse scheduling problem (NSP) is a complex optimization problem that allows for the preparation of an appropriate schedule for nurses and, in doing so, considers the system constraints such as legal regulations, nurses' preferences, and hospital policies and requirements. There are many studies in the literature that use exact solution algorithms, heuristics, and meta-heuristics approaches. Especially in large-scale problems, for which deterministic methods may require too much time and cost to reach a solution, heuristics and meta-heuristic approaches come to the fore instead of exact methods. In the first phase of the study, harmony search algorithm (HSA), which has shown progress recently and can be adapted to many problems is applied for a dataset in the literature, and the algorithm's performance is evaluated by comparing the results with other heuristics which is applied to the same dataset. As a result of the evaluation, the performance of the classical HSA is inadequate when compared to other heuristics. In the second phase of our study, by considering new approaches proposed by the literature for HSA, the effects on the algorithm's performance of these approaches are investigated and we tried to improve the performance of the algorithm. With the results, it has been determined that the improved algorithm, which is called opposition-based parallel HSA, can be used effectively for NSPs.

关键词： harmony search algorithm nurse scheduling problem meta-heuristics parallel grouping opposition-based learning

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harmony search algorithm with Adaptive Parameters to Optimize the Linear Quadratic Regulator Design

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IEEE LATIN AMERICA TRANSACTIONS 2018年第7期16卷 1862-1869页

作者： Nascimento, L. B. P. Pinto, V. P. Amora, M. A. B. Univ Fed Ceara Engn Eletr & Comp Sobral Ceara Brazil Univ Fed Ceara Curso Engn Eletr Campus Sobral Sobral Ceara Brazil Univ Fed Ceara Sobral Ceara Brazil

Linear Quadratic Regulator (LQR) is an important control technique with excellent properties associated to robust stability. This technique has been the subject of constant study until the present day, since the problems weighting matrices Q and R are still open, as well as the situations in which the dynamics is unknown. This work proposes the application of a novel harmony search (HS) algorithm to find the Q and R matrices. This algorithm ensures the automatic adjustment of parameters. By adopting the CH-47 helicopter and an inverted pendulum system, several tests involving search and simulations have been performed with two HS algorithms i.e. standard HS and Statistical Dispersion harmony search (SDHS). The latter one can be seen as the main contribution of this work, which also compares the results obtained from the algorithms.

关键词： Linear Quadratic Regulator harmony search algorithm Optimization Metaheuristic Intelligent Control

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An enhanced adaptive global-best harmony search algorithm for continuous optimization problems

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ENGINEERING REPORTS 2020年第11期2卷

作者： Yarmohamadi, Hasan Zhang, Qianyun Jiao, Pengcheng Alavi, Amir H. Univ Pittsburgh Dept Civil & Environm Engn Pittsburgh PA 15261 USA Zhejiang Univ Ocean Coll Inst Port Coastal & Offshore Engn Zhoushan Peoples R China Zhejiang Univ Engn Res Ctr Ocean Sensing Technol & Equipment Zhoushan Zhejiang Peoples R China Univ Pittsburgh Dept Bioengn Pittsburgh PA 15261 USA

This paper presents an enhanced adaptive global-best harmony search (EAGHS) to solve global continuous optimization problems. The global-best HS (GHS) is one of the strongest versions of the classical HS algorithm that hybridizes the concepts of swarm intelligence and conventional HS. However, randomized selection of harmony in the permissible interval diverts the GHS algorithm from the global optimum. To address this issue, the proposed EAGHS method introduces a dynamic coefficient into the GHS algorithm to increase the search power in early iterations. Various complex and extensively-applied benchmark functions are used to validate the developed EAGHS algorithm. The results indicate that the EAGHS algorithm offers faster convergence and better accuracy than the standard HS, GHS and other similar algorithms. Further analysis is performed to evaluate the sensitivity of the proposed method to the changes of parameters such as harmony memory consideration rate, harmony search memory, and larger dimensions.

关键词： continuous optimization global-best harmony search global optimization harmony search algorithm metaheuristics

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A Modified Global harmony search algorithm with Random Crossover for Continuous High Dimensional Optimization Problems 31

A Modified Global Harmony Search Algorithm with Random Cross...

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31st Chinese Control And Decision Conference (CCDC)

作者： Zhai, Junchang Qin, Yuping Zhang, Ping Bohai Univ Coll Informat Sci & Technol Jinzhou 121013 Peoples R China Bohai Univ Coll Engn Jinzhou 121013 Peoples R China Anshan Normal Univ Coll Phys & Technol Anshan 114005 Peoples R China

ISBN: (纸本)9781728101057

This paper proposes a modified global harmony search (MGHS) algorithm with random crossover algorithm to solve continuous high dimensional optimization problems. For the problem of premature convergence in harmony search algorithm, in the improvisation stage of MGHS algorithm, the new harmony vector is generated dynamically by means of random crossover for the global optimization problems, i.e., the worst harmony learning from the best harmony and the random selected other harmony learning from the best harmony random crossover strategy. Finally. MGHS algorithm is applied in the simulation test of 8 benchmark functions, the simulation results demonstrate the MGHS algorithm has higher convergence precision and convergence rate.

关键词： harmony search algorithm random crossover opposition-based learning

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Use of multi-criteria decision-making for selecting spillway type and optimizing dimensions by applying the harmony search algorithm: Qeshlagh Dam Case Study

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Lakes and Reservoirs: Science, Policy and Management for Sustainable Use 2019年第1期24卷 66-75页

作者： Hassanvand, Mohammad R. Karami, Hojat Mousavi, Sayed-Farhad Department of Water Engineering and Hydraulic Structures Faculty of Civil Engineering Semnan University Semnan Iran

Economic considerations are significantly important in designing a dam and its related hydraulic structures. Considering the methods used for economic design of hydraulic structures such as a spillway, they are also dependent on the construction costs of the spillway. In addition to the spillway type and capacity being associated with the magnitude of floods. Selecting different options of a spillway, considering all their aspects, has always been one of the biggest issues in decision-making. The present study determined the best spillway type (free-flow, stepped, semicircular and cylindrical) for Qeshlagh Dam, Iran, by considering different aspects (costs, time and performance) and using the TOPSIS method. The obtained dimensions of the spillway from multi-criteria decision-making were then optimized using meta-heuristic harmony search algorithm (HSA). The results identified a free-flow spillway was the best option in terms of cost and time, whereas a cylindrical spillway is the best choice in terms of performance. The optimal free-flow spillway length is 31.8 m, and height is 3.45 m, being capable of passing a flood discharge of 452 m ³ /s. This discharge was calculated by a reservoir routing method. Moreover, the obtained solution led to reducing the spillway construction costs, one of the most important issues in civil engineering projects. © 2018 John Wiley & Sons Australia, Ltd

关键词： construction costs harmony search algorithm multi-criteria decision-making optimizing spillway dimensions

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Climbing harmony search algorithm for Nurse Rostering Problems 3rd

Climbing Harmony Search Algorithm for Nurse Rostering Proble...

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3rd International Conference of Reliable Information and Communication Technology (IRICT)

作者： Hadwan, Mohammed Ayob, Masri Al-Hagery, Mohammed Al-Tamimi, Bassam Naji Qassim Univ Dept Informat Technol Qassim Buraidah 51452 Saudi Arabia Univ Kebangsaan Malaysia Fak Teknol Dan Sains Maklumat Ctr Artificial Intelligent CAIT Data Min & Optimisat Res Grp DMO Bangi 43600 Selangor Malaysia Qassim Univ Coll Comp Dept Comp Sci Qassim Buraidah 51452 Saudi Arabia Taibah Univ Coll Comp Sci & Engn Dept Informat Syst Medina Saudi Arabia

ISBN: (纸本)9783319990071;9783319990064

Nurse Rostering Problem (NRP) is a well-known NP-Hard combinatorial optimization problem. The fact is that coping real-world constraints in allocating the shift duties fairly among the available nurses is still a hard task to accomplish. The problem becomes more serious due to the shortage of nurses. Thus, this work aims to tackle this problem by hybridizing an Enhanced harmony search algorithm (EHSA) with the standard Hill climbing (HC). This hybridization may help to strike the balance between exploration and exploitation in the searching process. The proposed algorithm is called Climbing harmony search algorithm (CHSA) where it applied to solve a real-world NRP dataset, which arises at the Medical Center of Universiti Kebangsaan. The results show that CHSA performs much better than EHSA alone and Basic harmony search algorithm (BHSA) in all instances in terms of obtained penalty values (PVs), desirable patterns (DPs) and computational time as well.

关键词： Nurse Rostering Problem (NRP) harmony search algorithm Hill climbing algorithm Metaheuristic algorithms Optimization

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A Niching Multi-objective harmony search algorithm for Multimodal Multi-objective Problems

A Niching Multi-objective Harmony Search Algorithm for Multi...

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IEEE Congress on Evolutionary Computation (IEEE CEC)

作者： Qu, B. Y. Li, G. S. Guo, Q. Q. Yan, L. Chai, X. Z. Guo, Z. Q. Zhongyuan Univ Technol Sch Elect & Informat Engn Zhengzhou 450007 Henan Peoples R China Henan Xuchang Senior High Sch Xuchang 461000 Peoples R China

ISBN: (纸本)9781728121536

A modified multi-objective harmony search algorithm called Niching Multi-objective harmony search algorithm (NMOHSA) is proposed to solve multimodal multi-objective optimization problems. It adopts the neighborhood information to build dynamic harmony memory for maintaining the population diversity. A new memory consideration rule is also applied to prevent the algorithm be trapped into local optimal solution. Moreover, two key parameters, harmony memory consideration rate (HMCR) and pitch adjustment rate (PAR), are dynamically adjusted. Empirical results show that the proposed algorithm performs much better than the other existing multimodal multi-objective algorithms in terms of the solution quality.

关键词： Evolutionary algorithm multimodal multi-objective problems harmony search algorithm niching technique

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Pressure Vessel Design Simulation Using Hybrid harmony search algorithm 19

Pressure Vessel Design Simulation Using Hybrid Harmony Searc...

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Proceedings of the 3rd International Conference on Big Data Research

作者： Alaa A. Alomoush Mohammed I. Younis Khalid S. Aloufi AbdulRahman A. Alsewari Kamal Z. Zamli College of Computing and Applied Sciences Univiersiti Malaysia Pahang Pahang Malaysia Department of Computer Engineering College of Engineering University of Baghdad Iraq College of Computer Science and Engineering Taibah University Medina Saudi Arabia IBM Centre of Excellence College of Computing and Applied Sciences Univiersiti Malaysia Pahang Pahang Malaysia

ISBN: (纸本)9781450372015

Recently the development of optimization algorithm is rapidly increased. Among several optimization algorithms, harmony search (HS) has been recently proposed for solving engineering optimization problems. The HS has some weaknesses such as parameters selection and falling in local optima. Many variants proposed to solve these problems. This paper presents successful hybrid algorithms with high performance to solve the pressure vessel design simulation. The hybrid algorithms consist of well-known variants of HS and an opposition-based learning technique. The hybrid algorithm improved the HS exploration and avoiding falling in local optima, which lead the algorithm to provide significant results.

关键词： Computational Intelligence Pressure Vessel Design hybrid algorithm opposition-based learning harmony search algorithm Optimization algorithm

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P-HS-SFM: a parallel harmony search algorithm for the reproduction of experimental data in the continuous microscopic crowd dynamic models

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JOURNAL OF EXPERIMENTAL & THEORETICAL ARTIFICIAL INTELLIGENCE 2018年第2期30卷 235-255页

作者： Jaber, Khalid Mohammad Alia, Osama Moh'd Shuaib, Mohammed Mahmod Al Zaytoonah Univ Jordan Fac Sci & Informat Technol Amman Jordan Univ Tabuk Fac Comp & Informat Technol Dept Comp Sci Tabuk Saudi Arabia Al Imam Muhammad Ibn Saud Islamic Univ Coll Sharia & Islamic Studies Ahsaa Dept Comp Sci Al Ahsaa Saudi Arabia

Finding the optimal parameters that can reproduce experimental data (such as the velocity-density relation and the specific flow rate) is a very important component of the validation and calibration of microscopic crowd dynamic models. Heavy computational demand during parameter search is a known limitation that exists in a previously developed model known as the harmony search-Based Social Force Model (HS-SFM). In this paper, a parallel-based mechanism is proposed to reduce the computational time and memory resource utilisation required to find these parameters. More specifically, two MATLAB-based multicore techniques (parfor and create independent jobs) using shared memory are developed by taking advantage of the multithreading capabilities of parallel computing, resulting in a new framework called the Parallel harmony search-Based Social Force Model (P-HS-SFM). The experimental results show that the parfor-based P-HS-SFM achieved a better computational time of about 26h, an efficiency improvement of approximate to 54% and a speedup factor of 2.196 times in comparison with the HS-SFM sequential processor. The performance of the P-HS-SFM using the create independent jobs approach is also comparable to parfor with a computational time of 26.8h, an efficiency improvement of about 30% and a speedup of 2.137 times.

关键词： Parallel computing multi-threading harmony search algorithm continuous microscopic crowd dynamics social force model

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