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17th International Conference on Parallel Problem Solving from Nature (PPSN)

作者： Xie, Yue Neumann, Aneta Stanford, Ty Rasmussen, Charlotte Lund Dumuid, Dorothea Neumann, Frank Univ Adelaide Adelaide SA Australia Univ South Australia Allied Hlth & Human Performance Alliance Res Exercise Nutr & Act Adelaide SA Australia Norwegian Univ Sci & Technol Trondheim Norway Univ Limerick Dept Phys Educ & Sport Sci Limerick Ireland

ISBN: (纸本)9783031147210;9783031147203

How someone allocates their time is important to their health and well-being. In this paper, we show how evolutionary algorithms can be used to promote health and well-being by optimizing time usage. Based on data from a large population-based child cohort, we design fitness functions to explain health outcomes and introduce constraints for viable time plans. We then investigate the performance of evolutionary algorithms to optimize time use for four individual health outcomes with hypothetical children with different day structures. As the four health outcomes are competing for time allocations, we study how to optimize multiple health outcomes simultaneously in the form of a multi-objective optimization problem. We optimize one-week time-use plans using evolutionary multi-objective algorithms and point out the trade-offs achievable with respect to different health outcomes.

关键词： Real-world application Time-use optimization single-objective optimization Multi-objective optimization

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Disassembly Sequence Planning:A Survey

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IEEE/CAA Journal of Automatica Sinica 2021年第7期8卷 1308-1324页

作者： Xiwang Guo MengChu Zhou Abdullah Abusorrah Fahad Alsokhiry Khaled Sedraoui the College of Computer and Communication Engineering Liaoning Shihua UniversityFushun 113001China the Department of Electrical and Computer Engineering New Jersey Institute of TechnologyNewark NJ 07102 USA the Center of Research Excellence in Renewable Energy and Power Systems King Abdulaziz UniversityJeddah 21481Saudi Arabia the Department of Electrical and Computer Engineering Faculty of Engineeringand the Center of Research Excellence in Renewable Energy and Power SystemsKing Abdulaziz UniversityJeddah 21481Saudi Arabia

It is well-recognized that obsolete or discarded products can cause serious environmental pollution if they are poorly be *** contain reusable resource that can be recycled and used to generate desired economic ***,performing their efficient disassembly is highly important in green manufacturing and sustainable economic *** typical examples are electronic appliances and electromechanical/mechanical *** paper presents a survey on the state of the art of disassembly sequence *** can help new researchers or decision makers to search for the right solution for optimal disassembly *** reviews the disassembly theory and methods that are applied for the processing,repair,and maintenance of obsolete/discarded *** paper discusses the recent progress of disassembly sequencing planning in four major aspects:product disassembly modeling methods,mathematical programming methods,artificial intelligence methods,and uncertainty *** survey should stimulate readers to be engaged in the research,development and applications of disassembly and remanufacturing methodologies in the Industry 4.0 era.

关键词： Artificial intelligence(AI) disassembly sequence planning(DSP) intelligent optimization modeling methods multiobjective optimization single-objective optimization uncertainty.

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Prism refraction search: a novel physics-based metaheuristic algorithm

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JOURNAL OF SUPERCOMPUTING 2024年第8期80卷 10746-10795页

作者： Kundu, Rohit Chattopadhyay, Soumitri Nag, Sayan Navarro, Mario A. Oliva, Diego Jadavpur Univ Dept Elect Engn Kolkata India Jadavpur Univ Dept Informat Technol Kolkata India Univ Toronto Dept Med Biophys Toronto ON Canada Univ Guadalajara Dept Ingn Electrofoton CUCEI Guadalajara Mexico

single-solution-based optimization algorithms are computationally cheap yet powerful methods that can be used on various optimization tasks at minimal processing expenses. However, there is a considerable shortage of research in this domain, resulting in only a handful of proposed algorithms over the last four decades. This study proposes the Prism Refraction Search (PRS), a novel, simple yet efficient, single-solution-based metaheuristic algorithm for single-objective real-parameter optimization. PRS is a physics-inspired algorithm modeled on a well-known optimization paradigm in ray optics arising from the refraction of light through a triangular prism. The key novelty lies in its scientifically sound background that is supported by the well-established laws of physical optics. The proposed algorithm is evaluated on several numerical objectives, including 23 classical benchmark functions, the CEC-2017 test suite, and five standard real-world engineering design problems. Further, the results are analyzed using standard statistical tests to prove their significance. Extensive experiments and comparisons with state-of-the-art metaheuristic algorithms in the literature justify the robustness and competitive performance of the PRS algorithm as a lightweight and efficient optimization strategy.

关键词： Prism refraction Metaheuristic Physics-inspired single solution single-objective optimization Continuous search space

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Effects of processing parameters on electrode loss of micro-EDM milling with spiral electrode

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INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY 2022年第5-6期121卷 4011-4021页

作者： Xing, Qixuan Gao, Xiang Zhang, Qinhe Shandong Univ Sch Mech Engn Key Lab High Efficiency & Clean Mech Mfg Minist Educ Jinan 250061 Peoples R China Shandong Univ Natl Demonstrat Ctr Expt Mech Engn Educ Jinan 250061 Peoples R China

In order to uplift the machining efficiency and accuracy of micro electrical discharge machining (micro-EDM) milling, this paper studied the prediction and compensation method of electrode loss and established a fixed length compensation model for micro-EDM milling with spiral electrodes. It was verified through experiments that the model can successfully predict the electrode loss of micro-EDM milling with spiral electrodes. On the basis of a single factor experiment, the influence of processing parameters (pulse width, pulse interval, peak current, rotating speed) on the actual relative volume loss ratio (theta(r)) of micro-EDM milling with spiral electrodes was studied. Then, based on the orthogonal experiment, the optimization of the theta(r) of micro-EDM milling with spiral electrodes based on fixed length compensation was studied. Through signal-noise ratio (SNR) analysis, the optimal processing parameter combination of theta(r) was obtained as the pulse width of 4.2 mu s, the pulse interval of 13 mu s, the peak current of 4A, and the rotating speed of 1400r/min. Under this parameter combination, the theta(r) of micro-EDM milling with spiral electrodes based on fixed length compensation could be reduced to 22.23%. Variance analyses were carried out on the outcomes, and a process model of theta(r) based on fixed length compensation was established. Because the predicted results were consistent with the results of the validation test, the reliability of the process model was proved.

关键词： Micro-EDM Spiral electrode Fixed length compensation method Processing parameters single-objective optimization Process model

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From single- to multi-objective auto-tuning of programs: Advantages and implications

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SCIENTIFIC PROGRAMMING 2014年第4期22卷 285-297页

作者： Durillo, Juan Fahringer, Thomas Univ Innsbruck Inst Comp Sci A-6020 Innsbruck Austria

Automatic tuning (auto-tuning) of software has emerged in recent years as a promising method that tries to automatically adapt the behaviour of a program to attain different performance objectives on a given computing system. This method is gaining momentum due to the increasing complexity of modern multicore-based hardware architectures. Many solutions to auto-tuning have been explored ranging from simple random search to more sophisticate methods like machine learning or evolutionary search. To this day, it is still unclear whether these approaches are general enough to encompass all the complexities of the problem (e. g. search space, parameters influencing the search space, input data sensitivity, etc.), or which approach is best suited for a given problem. Furthermore, the growing interest in auto-tuning a program for several objectives is increasing this confusion even further. The goal of this paper is to formally describe the problem addressed by auto-tuning programs and review existing solutions highlighting the advantages and drawbacks of different techniques for single-objective as well as multi-objective auto-tuning approaches.

关键词： Program auto-tuning single-objective optimization multi-objective optimization

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Radio-frequency inductor synthesis using evolutionary computation and Gaussian-process surrogate modeling

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APPLIED SOFT COMPUTING 2017年 60卷 495-507页

作者： Passos, F. Roca, E. Castro-Lopez, R. Fernandez, F. V. Univ Seville CSIC IMSE CNM Inst Microelect Sevilla Calle Americo Vespucio S-N Seville 41092 Spain

In recent years, the application of evolutionary computation techniques to electronic circuit design problems, ranging from digital to analog and radiofrequency circuits, has received increasing attention. The level of maturity runs inversely to the complexity of the design task, less complex in digital circuits, higher in analog ones and still higher in radiofrequency circuits. Radiofrequency inductors are key culprits of such complexity. Their key performance parameters are inductance and quality factors, both a function of the frequency. The inductor optimization requires knowledge of such parameters at a few representative frequencies. Most common approaches for optimization-based radiofrequency circuit design use analytical models for the inductors. Although a lot of effort has been devoted to improve the accuracy of such analytical models, errors in inductance and quality factor in the range of 5%-25% are usual and it may go as high as 200% for some device sizes. When the analytical models are used in optimization-based circuit design approaches, these errors lead to suboptimal results, or, worse, to a disastrous non-fulfilment of specifications. Expert inductor designers rely on iterative evaluations with electromagnetic simulators, which, properly configured, are able to yield a highly accurate performance evaluation. Unfortunately, electromagnetic simulations typically take from some tens of seconds to a few hours, hampering their coupling to evolutionary computation algorithms. Therefore, analytical models and electromagnetic simulation represent extreme cases of the accuracy-efficiency trade-off in performance evaluation of radiofrequency inductors. Surrogate modeling strategies arise as promising candidates to improve such trade-off. However, obtaining the necessary accuracy is not that easy as inductance and quality factor at some representative frequencies must be obtained and both performances change abruptly around the self-resonance frequency, which

关键词： Surrogate models Evolutionary algorithms single-objective optimization Multi-objective optimization Integrated inductors

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Information Combining Schemes for Cooperative Spectrum Sensing: A Survey and Comparative Performance Analysis

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WIRELESS PERSONAL COMMUNICATIONS 2017年第3期94卷 685-711页

作者： Pradhan, Pyari Mohan Panda, Ganapati Indian Inst Technol Roorkee Dept Elect & Commun Engn Roorkee 247667 Uttar Pradesh India Indian Inst Technol Bhubaneswar Sch Elect Sci Bhubaneswar 751013 Odisha India

Spectrum scarcity has evolved as a challenging problem in the field of wireless communication. Cognitive radio (CR) has emerged as a solution to this problem which uses available spectrum efficiently in an opportunistic way. Spectrum sensing unit as part of a CR deals with the reliable detection of primary user's signal. However individual CRs do not able to detect the primary user due to factors such as noise uncertainty, multipath fading, shadowing etc. This paper presents a survey on state of the art information combining schemes for cooperative spectrum sensing. Different algorithms are employed for optimizing the probability of detection at a specified probability of false alarm. The performance of the state of the art techniques are compared with that achieved using evolutionary algorithm (EA). The simulation results show that the EAs perform better than the statistical techniques and reduce the computational complexity and time by a high margin. Different statistical tests are carried out to assess the stability of the simulation results offered by the heuristic EAs. In addition, the sensitivity analysis of different parameters is performed to demonstrate their impact on the overall performance of the system.

关键词： Spectrum sensing Cooperative sensing Cognitive radio Evolutionary algorithm single-objective optimization

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Some investigations into the optimal dimensional synthesis of parallel robots

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INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY 2016年第9-12期83卷 1525-1538页

作者： Kelaiaia, Ridha Zaatri, Abdelouahab Company, Olivier Chikh, Lotfi Univ 20 Aout 1955 Skikda Lab Genie Mecan & Mat PB 26 Route Elhadaik Skikda 21000 Algeria Univ Constantine1 Adv Technol Lab Constantine Algeria CNRS UM2 UMR 5506 Montpellier Lab Informat Robot & Microelect 161 Rue Ada F-34392 Montpellier 5 France Fatronik France Tecnalia Cap Omega Rond Point B Franklin F-34960 Montpellier France

In this paper, we will perform a comparison between two approaches of dimensional synthesis of parallel robots. The first one concerns the single-objective optimization approach;in this case, the dimensional synthesis is expressed by taking into account only one performance criterion but enables to get a final solution if it exists. The second one concerns the multi-objective optimization approach;it enables to simultaneously take into account several performance criteria. However, this approach appears to provide a set of solutions instead of a single expected final solution which should directly enable to carry out the structural synthesis. In fact, the search of a single final solution is postponed to a further step where the designers have to impose and/or restrict certain parameters. And we will establish if it is really necessary to make a multi-objective optimization approach or if a single-objective is sufficient to reach the objectives set in the specifications (user requirements). A discussion is proposed concerning the arising questions related to each approach and leading to the optimal dimensional synthesis. The PAR2 robot with two degree-of-freedom is used to exemplify the analysis and the comparison of the two approaches. The proposed comparison can be applied to any classes of parallel robots.

关键词： Dimensional synthesis single-objective optimization Multi-objective optimization Criteria of performance SQP Genetic algorithm NSGA-II PAR2 robot

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On the Performance of Different Genetic Programming Approaches for the SORTING Problem

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EVOLUTIONARY COMPUTATION 2015年第4期23卷 583-609页

作者： Wagner, Markus Neumann, Frank Urli, Tommaso Univ Adelaide Optimisat & Logist Adelaide SA Australia Univ Udine DIEGM I-33100 Udine Italy

In genetic programming, the size of a solution is typically not specified in advance, and solutions of larger size may have a larger benefit. The flexibility often comes at the cost of the so-called bloat problem: individuals grow without providing additional benefit to the quality of solutions, and the additional elements can block the optimization process. Consequently, problems that are relatively easy to optimize cannot be handled by variable-length evolutionary algorithms. In this article, we analyze different single- and multiobjective algorithms on the sorting problem, a problem that typically lacks independent and additive fitness structures. We complement the theoretical results with comprehensive experiments to indicate the tightness of existing bounds, and to indicate bounds where theoretical results are missing.

关键词： Computational complexity genetic programming variable-length representation sortedness single-objective optimization multiobjective optimization

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Investigating the modified thermoelectric generator system performance

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JOURNAL OF THERMAL ANALYSIS AND CALORIMETRY 2023年第21期148卷 11955-11968页

作者： Harb, Abd El-Moneim A. Elsayed, Khairy Kabeel, A. E. Ahmed, Mahmoud Abdo, Ahmed Helwan Univ Dept Mech Power Engn Fac Engn El Mattaria Helwan Egypt Tanta Univ Mech Power Engn Dept Fac Engn Tanta Egypt Egypt Japan Univ Sci & Technol Energy Resources Engn Dept Alexandria Egypt Assiut Univ Mech Engn Dept Assiut 71516 Egypt Delta Univ Sci & Technol Fac Engn Gamasa Egypt Islamic Univ Madinah Dept Mech Engn Medina 42351 Saudi Arabia

It is essential to enhance the performance of the thermoelectric generator as lower efficiencies are obtained recently. This could be achieved by changing its dimensions in addition to copper strip thickness. The present study is performed to obtain the best dimensions of the P-N legs considering the interaction between all variables. To do this, a comprehensive TEG model is achieved in addition to utilizing the single-objective optimization technique. The main performance metrics, including electricity production and conversion efficiency, are assessed, and contrasted with the conventional TEG system since the simulation. The length of the legs and their cross-sectional area were shown to significantly affect power production. The thickness of the conducting plate, in contrast, barely matters. For instance, a P-N pair with legs that have a 2 mm2 cross-sectional area generates 0.4 W and 1.3 W for temperature differences of 480 degrees C and 980 degrees C, respectively. Furthermore, the equivalent efficiencies are 4.41% and 6.73%, respectively. Using the genetic algorithm revealed that the ideal values for the leg cross section, leg length, and conducting plate thickness are 1.84 mm2, 0.5 mm, and 0.44 mm, respectively. Once compared to the conventional system, using the optimization method results in an improvement in power production and conversion efficiency of about 247% at a temperature differential of 980 degrees C.

关键词： Thermoelectric generator single-objective optimization Genetic algorithm Semiconductors Conversion efficiency

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