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Solving Biobjective Distributed Flow-Shop Scheduling Problems With Lot-Streaming Using an Improved jaya algorithm

IEEE TRANSACTIONS ON CYBERNETICS 2023年第6期53卷 3818-3828页

作者： Pan, Yuxia Gao, Kaizhou Li, Zhiwu Wu, Naiqi Macau Univ Sci & Technol Inst Syst Engn Macau Peoples R China Macau Univ Sci & Technol Collaborat Lab Intelligent Sci & Syst Macau Peoples R China Univ Sanya Sch Informat & Intelligence Engn Sanya 572000 Hainan Peoples R China

A distributed flow-shop scheduling problem with lot-streaming that considers completion time and total energy consumption is addressed. It requires to optimally assign jobs to multiple distributed factories and, at the same time, sequence them. A biobjective mathematic model is first developed to describe the considered problem. Then, an improved jaya algorithm is proposed to solve it. The Nawaz-Enscore-Ham (NEH) initializing rule, a job-factory assignment strategy, the improved strategies for makespan and energy efficiency are designed based on the problem's characteristic to improve the jaya's performance. Finally, experiments are carried out on 120 instances of 12 scales. The performance of the improved strategies is verified. Comparisons and discussions show that the jaya algorithm improved by the designed strategies is highly competitive for solving the considered problem with makespan and total energy consumption criteria.

关键词： Production facilities Job shop scheduling Mathematical models Energy consumption Indexes Collaboration Memetics Flow-shop scheduling jaya algorithm lot-streaming makespan total energy consumption

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Allocation of DG in Distribution Network Using Parameter Independent jaya algorithm

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JOURNAL OF ELECTRICAL ENGINEERING & TECHNOLOGY 2023年第3期18卷 1675-1692页

作者： Pandey, Anand Kumar Kirmani, Sheeraz Kumar, Ankesh Akhtar, Iram JSS Acad Techinal Educ Elect & Elect Engn Noida India Aligarh Muslim Univ Elect Engn Aligarh India Jamia Millia Islamia Elect Engn New Delhi India

Integration of DGs in the distribution network has led to challenges in making the system reliability, and other parameters improve. This paper gives a detailed discussion on the placement of DG in the distribution system using the new algorithm 'jaya' having no control parameter which makes the algorithm simple than previous used algorithms and also give best solutions according to the study. Three system parameters are considered for DG placement solution: active power loss reduction, voltage deviation reduction and voltage stability index maximization. The methodology is presented to calculate the optimal values for varying load profiles i.e. constant, residential, commercial and industrial. Type-1 DG placement is considered for placement. Simultaneous improvement of all factors using weight based multi-objective function is used. Standard test system IEEE-33 and 69 bus is used to validate the applicability of the methodology and compared to other optimization methods, the results presented proves the jaya to be better optimization of optimal DG calculation as the method is simple, feasible and have good applicability with other nature inspired and meta-heuristic methods.

关键词： jaya algorithm Distributed generation Power system optimization Distribution system

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Structural damage identification with output-only measurements using modified jaya algorithm and Tikhonov regularization method

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SMART STRUCTURES AND SYSTEMS 2023年第3期31卷 229-245页

作者： Zhang, Guangcai Wan, Chunfeng Xie, Liyu Xue, Songtao Southeast Univ Key Lab concrete & prestressed concrete Struct Minist Educ Nanjing Peoples R China Tongji Univ Res Inst Struct Engn & Disaster Reduct Coll Civil Engn Shanghai Peoples R China Tohoku Inst Technol Dept Architecture Sendai Japan

The absence of excitation measurements may pose a big challenge in the application of structural damage identification owing to the fact that substantial effort is needed to reconstruct or identify unknown input force. To address this issue, in this paper, an iterative strategy, a synergy of Tikhonov regularization method for force identification and modified jaya algorithm (M-jaya) for stiffness parameter identification, is developed for damage identification with partial output-only responses. On the one hand, the probabilistic clustering learning technique and nonlinear updating equation are introduced to improve the performance of standard jaya algorithm. On the other hand, to deal with the difficulty of selection the appropriate regularization parameters in traditional Tikhonov regularization, an improved L-curve method based on B-spline interpolation function is presented. The applicability and effectiveness of the iterative strategy for simultaneous identification of structural damages and unknown input excitation is validated by numerical simulation on a 21-bar truss structure subjected to ambient excitation under noise free and contaminated measurements cases, as well as a series of experimental tests on a five-floor steel frame structure excited by sinusoidal force. The results from these numerical and experimental studies demonstrate that the proposed identification strategy can accurately and effectively identify damage locations and extents without the requirement of force measurements. The proposed M-jaya algorithm provides more satisfactory performance than genetic algorithm, Gaussian bare-bones artificial bee colony and jaya algorithm.

关键词： B-spline interpolation function damage identification force identification jaya algorithm k-means clustering Tikhonov regularization

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Modified jaya algorithm with depth search and perturbation

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INTERNATIONAL JOURNAL OF COMPUTING SCIENCE AND MATHEMATICS 2023年第3期17卷 276-283页

作者： Liu, Xiang Tang, Jun Hunan Urban Construction Coll Dept Architectural Engn Xiangtan 411101 Peoples R China Hunan Urban Construction Coll Dept Construction Equipment Engn Xiangtan 411101 Peoples R China

This paper presents a modified jaya algorithm with depth search and perturbation to solve numerical optimisation problems. The new jaya approach (called MDPjaya) consists of two improved strategies. First, the original search equation is modified by introducing a random solution. Second, a Cauchy perturbation based on the depth search is used to strengthen the global search ability. To validate the optimisation capability of MDPjaya, some famous benchmark optimisation problems are tested. Simulation results show MDPjaya can achieve better solutions than the standard jaya algorithm.

关键词： jaya algorithm modified search equation Cauchy perturbation depth search numerical optimisation

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Multi-response Optimization of Electro-Discharge Machining Parameters by Using jaya algorithm for Thin Wire-Arc Additive Manufactured IN625 Surface 4th

Multi-response Optimization of Electro-Discharge Machining P...

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4th International Conference on Advanced Engineering Optimization Through Intelligent Techniques

作者： Motwani, Amit Puri, Y. M. Koppu, Anand Kumar Vamsi, Pilligoila Krishna Visvesvaraya Natl Inst Technol Nagpur 440010 Maharashtra India

ISBN: (纸本)9789819796618;9789819746545;9789819746538

Wire-arc additive manufacturing (WAAM) often exhibits lower shape accuracy compared to other metal additive manufacturing techniques. Layer deposition results in a distinct surface profile that requires additional machining to achieve the desired final part. Conventional machining systems face challenges on finishing the thin features or harder alloys produced through WAAM. In this study, a 5.5 mm thin nonuniform surface of Inconel 625 superalloy prepared by the WAAM process is machined using electro-discharge machining (EDM) as an alternate post-processing technique. The study investigates the effects of process parameter's and its optimization for individual responses by using Taguchi analysis and a population-based meta-heuristic technique of jaya algorithm. The varying parameters selected were pulse-on time (T-on), pulse-off time (T-off), peak current (I-p), and gap voltage (V-g) for the responses of material removal rate (MRR) and surface roughness (SR). Further, the objective to achieve the multi-response optimization considering the MRR and SR as equally important factors is also performed by using the jaya algorithm. Optimum EDM parameters for normalized multi-response function obtained by jaya algorithm were T-on = 5 mu s, T-off = 8 mu s, I-p = 8 A, V-g = 25 V. The experimental MRR and SR for optimized parameters were calculated as 6.861 mm(3)/min and 3.79 Ra with the prediction error of 10.78% and 5.67%, respectively. The developed models were experimentally validated and demonstrated satisfactory performance, despite considerable prediction errors. This investigation provides essential insights into controlling the EDM process for post-processing the WAAM surfaces.

关键词： WAAM Post-process machining EDM jaya algorithm Multi-response optimization

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Application of the Improved jaya algorithm in Searching the Worst Mistuning Patterns for the Splittered Impeller

Application of the Improved JAYA Algorithm in Searching the ...

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Asia-Pacific International Symposium on Aerospace Technology (APISAT)

作者： Liu, Kaicheng Liu, Zhaoyu Yan, Yingliang Beijing Aerosp Prop Inst Beijing 100176 Peoples R China Lab Cryogen Liquid Prop Technol Beijing 100176 Peoples R China

ISBN: (纸本)9789819740123;9789819740109;9789819740093

To investigate the worst mistuning pattern of the impeller with splitter blades, the parallel multipopulation-based elitist jaya (PME-jaya) algorithm is proposed based on the original jaya algorithm, which is a new metaheuristic algorithm and has a very simple structure. Compared with the original jaya, the PME-jaya increases the diversity of the search process and improves the population quality by introducing the multipopulation search mechanism and the elite selection strategy, and which accelerates the convergence of the algorithm. At the same time, the parallel computing capability of the algorithm during the process of updating subpopulations is developed, which improves the computing efficiency. Using the PME-jaya, the worst mistuning patterns of the impeller are searched for the following typical cases of mistuning distribution: (i) the mistuning only distributes on main blades. (ii) the mistuning only distributes on splitter blades. (iii) the mistuning distributes on both main and splitter blades with larger amplitude for the main blades. The forced response characteristics are compared and the influence of mistuning amplitude on the vibration localization characteristics in the worst mistuning cases are analyzed. The results show the main blade dominated modes are sensitive to the main blade mistuning, but not to the splitter blade mistuning. And the splitter blades have the similar property. When mistuning follows uniform distribution, the worst mistuning pattern search results indicate multiple blades have reached the set mistuning amplitude and the worst mistuning patterns under different mistuning amplitudes are not the same. Besides, the position where the maximum response occurs is not fixed for some specific blade.

关键词： jaya algorithm Mistuned Impeller Splitter Blade Worst Mistuning

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Harmonic State and Power Flow Estimation in Distribution Systems Using jaya algorithm 18

Harmonic State and Power Flow Estimation in Distribution Sys...

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IEEE 18th International Conference on Compatibility, Power Electronics and Power Engineering (CPE-POWERENG)

作者： Sepulchro, Walace do Nascimento Encarnacao, Lucas Frizera Univ Fed Espirito Santo Dept Elect Engn Vitoria ES Brazil

ISBN: (纸本)9798350318272;9798350318265

The massive use of nonlinear loads that directly impact the levels of harmonic distortion in the electrical systems and the high cost of power quality meters pose challenges in locating and mitigating harmonic pollution sources. In this context, a new methodology for harmonic state estimation and power flow based on the jaya algorithm is proposed, and the results are compared with the already employed methodology based on Evolutionary Strategies. The simulation results using jaya algorithm has a lower average error and computational effort using fewer input parameters when compared to the Evolutionary Strategies algorithm.

关键词： harmonic state estimation power quality power flow Evolutionary Strategy jaya algorithm

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Discrete Structural Optimization with Set-Theoretical jaya algorithm

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IRANIAN JOURNAL OF SCIENCE AND TECHNOLOGY-TRANSACTIONS OF CIVIL ENGINEERING 2023年第1期47卷 79-103页

作者： Kaveh, Ali Hamedani, Kiarash Biabani Iran Univ Sci & Technol Sch Civil Engn IUST POB 16846-13114 Tehran Iran

Discrete optimization of structures is known as a complex optimization problem with many local optima. Since metaheuristic algorithms do not require gradient information of the objective function and constraints, they are suitable for discrete optimization problems. A recently developed version of the jaya algorithm (JA), called set-theoretical jaya algorithm (ST-JA), has proven its effectiveness and robustness in solving structural optimization problems with continuous search spaces. In this paper, the ST-JA is applied to the discrete optimization of truss structures under stress and displacement constraints. The main idea of ST-JA is based on the division of the population of solutions into smaller well-arranged subpopulations of the same size. It follows that different subpopulations have different best and worst solutions. In this way, the ST-JA aims to strengthen both the exploration and exploitation capabilities of the classical JA and strike a balance between them. The performance of the ST-JA is demonstrated through four well-known truss optimization problems with discrete design variables, and its results are compared with those of the classical JA as well as other metaheuristic algorithms in the literature. To the best of our knowledge, this is the first time to apply ST-JA to discrete structural optimization. Numerical results reveal that ST-JA significantly outperforms the classical JA, especially in terms of convergence speed and accuracy, and provides results superior to other state-of-the-art metaheuristics.

关键词： Metaheuristics jaya algorithm Set-theoretical jaya algorithm Discrete structural optimization Discrete design variables Truss structures

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jaya algorithm- a practical algorithm for solving economic load dispatch problems

Jaya Algorithm- a practical algorithm for solving economic l...

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International Conference on Energy and Power Engineering (ICEPE)

作者： Fahim, Khairul Eahsun Yassin, Hayati De Silva, Liyanage C. Roy, Tanmoy Rihan, Naahi Mumtaj Tanvir, Mohammad Anjum Univ Brunei Darussalam Bandar Seri Begawan Brunei ZNRF Univ Management Sci Dhaka Bangladesh Univ Brunei Daussalam Fac Integrated Technol Bandar Seri Begawan Brunei Anwer Khan Modern Univ EEE Dept Dhaka Bangladesh BRAC Univ EEE Dept Dhaka Bangladesh Nanchang Hangkong Univ Aeronaut Engn Nanchang Jiangxi Peoples R China

ISBN: (纸本)9781665455770

A power system's generation, transmission, and distribution components all require some form of optimization to ensure efficiency, quality, safety, and stability. One of the critical issues in designing and managing an electric power generation system is the efficient scheduling of all power generation facilities to satisfy the increasing demand for electricity. Dynamic economic load dispatch includes a strategy for optimizing fuel usage. It can operate at its best by correctly scheduling the generator following the load requirement. The Lagrange multiplier method and Genetic algorithm, as well as assessments using the jaya algorithm, are compared in this research to find the lowest fuel cost while considering valve point effects. The suitability of the jaya algorithm for economic load dispatch has not been explored in much literature. So, one of this paper's prime objectives is to determine the suitability of the jaya algorithm for the real-world economic load dispatch problem.

关键词： Economic Load Dispatch (ELD) Genetic algorithm (GA) Lagrange Multiplier Method jaya algorithm

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Training Multilayer Perceptron: A Comparison of Back-propagation and Enhanced jaya algorithm for Data Classification 4th

Training Multilayer Perceptron: A Comparison of Back-propaga...

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4th International Conference on Advanced Engineering Optimization Through Intelligent Techniques

作者： Mohapatra, Swagatika Sarangi, Partha Pratim Dash, Jyotiprakash Mishra, Bhabani Shankar Prasad KIIT Deemed Be Univ Sch Comp Engn Bhubaneswar Odisha India

ISBN: (纸本)9789819796618;9789819746545;9789819746538

Choosing the most suitable weights and bias for feed-forward neural networks plays a critical role in the process of data classification. The back-propagation algorithm, commonly used in the multilayer perceptron, can get stuck in the local minima, resulting in poor generalization for data classification. To address this issue and improve accuracy, researchers have explored metaheuristic algorithms as replacements for back-propagation in the training of multilayer perceptron. However, many metaheuristic algorithms suffer from unsatisfactory performance due to the need for tuning a large number of control parameters and potential premature convergence. This paper introduces an effective jaya global optimization algorithm for training multilayer perceptron, which is both efficient and does not require manual adjustment of control parameters. To strike a balance between exploiting and exploring the solution space in the jaya algorithm, we present an enhanced version that offers an optimal configuration of connection weights to enhance the accuracy of the multilayer perceptron. Through extensive experiments using five well-known standard medical datasets, we demonstrate that the proposed method outperforms the jaya algorithm and traditional back-propagation algorithm in terms of performance accuracy.

关键词： Feed-forward neural networks Multilayer perceptron Metaheuristic algorithm jaya algorithm

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