Relevant bibliographies by topics / Load planning algorithm

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Book chapters
  4. Conference papers
  5. Reports

Academic literature on the topic 'Load planning algorithm'

Author: Grafiati
Published: 4 June 2025
Last updated: 15 July 2025

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Journal articles on the topic "Load planning algorithm"

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Wang, Yaoying, Shudong Sun, and Zhiqiang Cai. "The Research of Short-term Electric Load Forecasting based on Machine Learning Algorithm." Advances in Engineering Technology Research 4, no. 1 (2023): 334. http://dx.doi.org/10.56028/aetr.4.1.334.2023.

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The ability of electric load forecasting become the key to measuring electric planning and dispatching, and improving the accuracy of electric load forecasting has become one hot spot topic of scholars in recent years. The traditional electric load forecasting algorithm mainly include statistical learning algorithm. The electric load forecasting algorithm based on traditional forecasting algorithm, machine learning algorithm and neural network algorithm greatly improve the convergence approximation effect and accuracy. In recent years, the electric load forecasting algorithms based on the deep
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Kwiatoń, Paweł, Dawid Cekus, Dorian Skrobek, Michal Šofer, and Zdenek Poruba. "Path Planning Optimization of the Load Transport Process Using Heuristic Algorithms." Applied Sciences 14, no. 21 (2024): 9940. http://dx.doi.org/10.3390/app14219940.

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The paper presents the process of optimizing the duty cycle of a rotary crane. The minimization of the carried load’s trajectory was chosen as the objective function. The research was conducted using the genetic algorithm and the particle swarm algorithm. The influence of particular algorithm parameters on the obtained optimal solution was characterized. For the obtained best case, the inverse kinematics problem was solved, allowing us to determine the control functions of individual crane members. The presented redundant system was solved with the use of an algorithm for temporarily limiting
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Algashami, Abdullah M. "Algorithms for the executable programs planning on supercomputers." PLOS ONE 17, no. 9 (2022): e0275099. http://dx.doi.org/10.1371/journal.pone.0275099.

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This research dealt with the problem of scheduling applied to the supercomputer’s execution. The goal is to develop an appreciated algorithm that schedules a group of several programs characterized by their time consuming very high on different supercomputers searching for an efficient assignment of the total running time. This efficient assignment grantees the fair load distribution of the execution on the supercomputers. The essential goal of this research is to propose several algorithms that can ensure the load balancing of the execution of all programs. In this research, all supercomputer
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Quan, Zhaolong, Jie Xing, and Ruilin Cao. "A Multilayer Path Planning Method for High Voltage Distribution Network Based on the Floyd-Warshall Algorithm." Journal of Physics: Conference Series 2121, no. 1 (2021): 012006. http://dx.doi.org/10.1088/1742-6596/2121/1/012006.

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Abstract With the development of the city, a huge number of distribution networks are waiting for planning. A reasonable planning scheme can meet the power demand and reduce the investment cost. In this paper, a life cycle cost model including the investments of substation and wiring is established with the constraints about load flow calculation and maxi-mum load of wiring. Additionally, a multilayer planning method based on the Floyd-Warshall algorithm has been proposed to solve the model. The area of the city containing substations is divided based on the position of load through the hybrid
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Park, Rae-Jun, Kyung-Bin Song, and Bo-Sung Kwon. "Short-Term Load Forecasting Algorithm Using a Similar Day Selection Method Based on Reinforcement Learning." Energies 13, no. 10 (2020): 2640. http://dx.doi.org/10.3390/en13102640.

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Short-term load forecasting (STLF) is very important for planning and operating power systems and markets. Various algorithms have been developed for STLF. However, numerous utilities still apply additional correction processes, which depend on experienced professionals. In this study, an STLF algorithm that uses a similar day selection method based on reinforcement learning is proposed to substitute the dependence on an expert’s experience. The proposed algorithm consists of the selection of similar days, which is based on the reinforcement algorithm, and the STLF, which is based on an artifi
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Wang, Kailiang, Zhuoyi He, Jianpeng Ye, Yihan Lin, Lingxue Lin, and Yuxin Ma. "The Capacity-to-load ratio optimization method considering collaborative planning of multi-voltage level power grids." Journal of Physics: Conference Series 2703, no. 1 (2024): 012046. http://dx.doi.org/10.1088/1742-6596/2703/1/012046.

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Abstract The capacity-to-load ratio is an important indicator to guide power grid planning and has a decisive influence on the selection of substation capacities and the construction of power lines. A capacity-to-load ratio optimization method concerning collaborative planning of multi-voltage level power grids is proposed in this paper. This method aims to minimize the construction cost and takes into account the collaborative planning of substations and power lines of multiple voltage levels. By combining the Bayesian optimization algorithm (BOA) and genetic algorithms (GA), a BOA-GA solving
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Somchit, Siripat, Sirorat Pattanapairoj, and Rongrit Chatthaworn. "Improved Binary Differential Evolution for Transmission Expansion Planning." E3S Web of Conferences 629 (2025): 06003. https://doi.org/10.1051/e3sconf/202562906003.

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Increasing load and penetrating solar PhotoVoltaic (PV) systems tend higher in the future. Transmission Expansion Planning (TEP) is commonly used to solve this issue and is typically formed by using the peak load scenario, which is often assumed to represent the worst-case condition. Metaheuristic algorithms are predominantly used to address the TEP problem, which is frequently characterized by solutions becoming trapped in local optima. To address this challenge, this study proposes a TEP approach, utilizing an improved Binary Differential Evolution (BDE) algorithm in which the mutation facto
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Rakhmonov, I. U., and K. M. Reymov. "Mathematical Models and Algorithms of Optimal Load Management of Electricity Consumers." ENERGETIKA. Proceedings of CIS higher education institutions and power engineering associations 62, no. 6 (2019): 528–35. http://dx.doi.org/10.21122/1029-7448-2019-62-6-528-535.

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Load profile alignment based on optimal power consumption management is considered to be one of the main ways to ensure efficient operation of energy systems in the short-term planning. Alignment load profile with a view to reducing costs can be implemented with the aid of consumers’ involvement by administrative and economic measures. Administrative measures are associated with the forced restriction of consumer loads in certain intervals of the planning period. On one hand, these measures provide benefits to the power system by alignment load profile, and on the other hand, they cause detrim
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Reymov, K. M., G. M. Turmanova, S. K. Makhmuthonov, and B. A. Uzakov. "Mathematical models and algorithms of optimal load management of electrical consumers." E3S Web of Conferences 216 (2020): 01166. http://dx.doi.org/10.1051/e3sconf/202021601166.

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The article investigated the static, dynamic and metrological characteristics of new magnetoelastic force sensors taking into account the distribution of Load profile smoothing based on optimal power management is considered to be one of the main ways to ensure efficient operation of energy systems in the short-term planning. Smoothing load profile with a view to reducing costs can be implemented on the ways in which consumers could be affected by administrative and economic measures. Administrative measures are associated with the forced restriction of consumer loads in certain intervals of t
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Thapliyal, Nitin, and Priti Dimri. "Load Balancing in Cloud Computing Based on Honey Bee Foraging Behavior and Load Balance Min-Min Scheduling Algorithm." International Journal of Electrical and Electronics Research 10, no. 1 (2022): 1–6. http://dx.doi.org/10.37391/ijeer.100101.

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Cloud computing relies on the collection and distribution of services from internet-based data centers. With the large resource pool available in internet wide range of users are accessing the cloud. Load balance is important feature involving resource allocation to prevent overloading of any system or optimal use of resources. Major load in cloud network are concerned with CPU, memory and network. This cloud computing aspect has not yet earned too much coverage. Although load balancing is an important feature for cloud computing, concurrent computing etc. In these areas, several algorithms we
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Dissertations / Theses on the topic "Load planning algorithm"

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Borges, Guilherme Pereira. "Metodologia para planejamento de ações de alívio de carregamento em sistemas de distribuição de energia elétrica em média tensão." Universidade de São Paulo, 2016. http://www.teses.usp.br/teses/disponiveis/18/18154/tde-02082017-165127/.

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O objetivo desta tese é desenvolver e implementar em computador uma metodologia para resolver o problema de alívio de carregamento utilizando técnicas de remanejamento ou corte de carga. Tal metodologia, fundamenta-se no Algoritmo Evolutivo Multiobjetivo em Tabelas, que foi desenvolvido inicialmente para o problema de restabelecimento de energia em sistemas de distribuição. Já metodologia desenvolvida nesta tese trata o problema de alívio de carregamento, buscando minimizar o número de consumidores sem fornecimento de energia elétrica e o número de operações de chaveamento. Todavia, é necessár
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Antoniadis, Antonios. "Scheduling algorithms for saving energy and balancing load." Doctoral thesis, Humboldt-Universität zu Berlin, Mathematisch-Naturwissenschaftliche Fakultät II, 2012. http://dx.doi.org/10.18452/16566.

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Diese Arbeit beschäftigt sich mit Scheduling von Tasks in Computersystemen. Wir untersuchen sowohl die in neueren Arbeiten betrachtete Zielfunktion zur Energieminimierung als auch die klassische Zielfunktion zur Lastbalancierung auf mehreren Prozessoren. Beim Speed-Scaling mit Sleep-State darf ein Prozessor, der zu jedem Zeitpunkt seine Geschwindigkeit anpassen kann, auch in einen Schlafmodus übergehen. Unser Ziel ist es, den Energieverbrauch zu minimieren. Wir zeigen die NP-Härte des Problems und klären somit den Komplexitätsstatus. Wir beweisen eine untere Schranke für die Approximationsg
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Yu, Chih-Ting, and 余致廷. "Optimal Planning of Power System Underfrequency Load Shedding Using Immune Algorithm." Thesis, 2010. http://ndltd.ncl.edu.tw/handle/zv2f4b.

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碩士<br>國立臺北科技大學<br>電機工程系研究所<br>98<br>When a power system experiences malfunctions, the power generator may trip and the transmission lines may break down, resulting in a load far exceeding the generated power. In such a situation, the generator’s attempt to increase its output can lead to a drastic drop in the system frequency. There is, however, a cap on the decline of frequency for each generator. Failure to facilitate instant recovery of frequency may reduce the generator’s life; the system may even collapse due to huge contingencies or generator tripping. Underfrequency relays are therefore
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Chen, Chun-Ju, and 陳俊儒. "Optimal Planning of Power System Underfrequency Load Shedding Using Genetic Algorithm." Thesis, 2008. http://ndltd.ncl.edu.tw/handle/xhscr2.

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碩士<br>國立臺北科技大學<br>電機工程系研究所<br>96<br>The system frequency will be declined rapidly and even system collapsed due to huge contingencies or generator trippings. The suitable shedding strategy is needed to use, therefore to avoid the fault areas expansion and recover the system by shedding the part of load. This thesis analysis the system underfrequency responses for simplified system of single machine infinite bus, and proposes genetic algorithm to do the setting of optimal underfrequency load shedding, each section of shedding frequency and shedding rate. This thesis aims to plan the setting of
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Liu, Jeng-Shang, and 劉正善. "Optimal Planning of Power System Underfrequency Load Shedding Using Hybrid Taguchi-Immune Algorithm." Thesis, 2011. http://ndltd.ncl.edu.tw/handle/74tgy3.

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碩士<br>國立臺北科技大學<br>電機工程系所<br>99<br>Taipower system, unlike the interconnected system in North America region being quite stable, is independent thus its frequency can easily be interfered. When the incident is minor, the power system can be stabilized with automatic power control or emergency power system. However, when there is major incident such as power plant generator unit tripping or power system tie line tripping, serious imbalance between loads of supply-and-demand will result in rapid drop of frequency. This would not only damage related power devices, but also affect the quality of p
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Lee, Ruey-Chung, and 李睿中. "A Social Spider Algorithm for Optimal Planning of Underfrequency Load Shedding on Power System." Thesis, 2018. http://ndltd.ncl.edu.tw/handle/awrv7b.

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碩士<br>國立臺北科技大學<br>電機工程系<br>107<br>When power generator units are tripped or experience a serious accident, the frequency drops quickly and the power system collapses. Using load-shedding will avoid an accident becoming worse. In order to keep the frequency in safe operating range when the accident happened in a single machine system, we use rate of change of frequency(ROCOF) relay and find out its corresponding decrease rate of frequency and rate of load-shedding. We also use social spider algorithm to find the best load-shedding quantity. A social spider algorithm imitates foraging cooperativ
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黃柏東. "The Application of Genetic Algorithm Approach on Load Transfer Substations Planning in Primary Distribution Systems." Thesis, 2011. http://ndltd.ncl.edu.tw/handle/41997014578331563959.

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碩士<br>建國科技大學<br>電機工程系暨研究所<br>99<br>This thesis proposes a genetic algorithm-based (GA-Based) approach for planning load transfer substations (LTSs). Firstly, the types and operations of the primary distribution system were discussed completely, and then the operations of four typical types of normally-closed loop feeders under contingencies were also discussed and analyzed. Although the typical Type I normally closed-loop feeder can eliminate the outage due to fault occurred in primary feeder, once the fault occurred in the upstream system the customer can’t avoid outage. Therefore, the load t
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Book chapters on the topic "Load planning algorithm"

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Mühlbauer, Matthias, Hubert Würschinger, Dominik Polzer, and Nico Hanenkamp. "Energy Profile Prediction of Milling Processes Using Machine Learning Techniques." In Machine Learning for Cyber Physical Systems. Springer Berlin Heidelberg, 2020. http://dx.doi.org/10.1007/978-3-662-62746-4_1.

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AbstractThe prediction of the power consumption increases the transparency and the understanding of a cutting process, this delivers various potentials. Beside the planning and optimization of manufacturing processes, there are application areas in different kinds of deviation detection and condition monitoring. Due to the complicated stochastic processes during the cutting processes, analytical approaches quickly reach their limits. Since the 1980s, approaches for predicting the time or energy consumption use empirical models. Nevertheless, most of the existing models regard only static snapshots and are not able to picture the dynamic load fluctuations during the entire milling process. This paper describes a data-driven way for a more detailed prediction of the power consumption for a milling process using Machine Learning techniques. To increase the accuracy we used separate models and machine learning algorithms for different operations of the milling machine to predict the required time and energy. The merger of the individual models allows finally the accurate forecast of the load profile of the milling process for a specific machine tool. The following method introduces the whole pipeline from the data acquisition, over the preprocessing and the model building to the validation.
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Yan, Xiaodong, and Cong Zhou. "Ascent Predictive Guidance for Thrust Drop Fault of Launch Vehicles Using Improved GS-MPSP." In Autonomous Trajectory Planning and Guidance Control for Launch Vehicles. Springer Nature Singapore, 2023. http://dx.doi.org/10.1007/978-981-99-0613-0_3.

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AbstractIncreasing complex space missions require launch vehicles to be with greater load-carrying capacity, better orbit injection accuracy and higher reliability. Such demands also cause the increased complexity of the vehicle, leading to a higher probability of fault, especially for the propulsion system. To remedy this issue, an advanced and robust ascent guidance capable of fault-tolerant is critical for the success of mission. Iterative guidance method [1] (IGM) and powered explicit guidance [2] (PEG) are two commonly used methods for the ascent phase of launch vehicles. These two guidance methods work well in the nominal condition and can adapt to many off-nominal conditions [3]. However, they lack of strong adaptive capacity, which cannot guarantee the reliability when the dynamic model or parameters change significantly. Alternatively, numerical approaches based on the optimal control theory may be the better choice. The existing algorithms can be divided into direct methods and indirect methods. Using the indirect methods, the guidance problem is transformed into Hamilton two-point boundary value problems [4] (TPBVP), but the solving process of this Hamilton two-point boundary value problem is complicated and highly sensitive to the initial guess. Using the direct method, the guidance problem is transformed into a nonlinear programming problem [5] (NLP). However, solving such problem is extremely computational intensive, which is difficult to meet the real-time requirement for online application.
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Anwar, Adnan, Md Apel Mahmud, Md Jahangir Hossain, and Himanshu Roy Pota. "Distributed Generation Capacity Planning for Distribution Networks to Minimize Energy Loss." In Advances in Computer and Electrical Engineering. IGI Global, 2016. http://dx.doi.org/10.4018/978-1-4666-9911-3.ch005.

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This chapter presents an unbalanced multi-phase optimal power flow (UMOPF) based planning approach to determine the optimum capacities of multiple distributed generation units in a distribution network. An adaptive weight particle swarm optimization algorithm is used to find the global optimum solution. To increase the efficiency of the proposed scheme, a co-simulation platform is developed. Since the proposed method is mainly based on the cost optimization, variations in loads and uncertainties within DG units are also taken into account to perform the analysis. An IEEE 123 node distribution system is used as a test distribution network which is unbalanced and multi-phase in nature, for the validation of the proposed scheme. The superiority of the proposed method is investigated through the comparisons of the results obtained that of a Genetic Algorithm based OPF method. This analysis also shows that the DG capacity planning considering annual load and generation uncertainties outperform the traditional well practised peak-load planning.
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Sahun, Yelyzaveta, Yuliya Sikirda, and Oleksandr Tymochko. "Application of Computer Load Optimization Model in an Aircraft Load Planning Process." In Encyclopedia of Information Science and Technology, Sixth Edition. IGI Global, 2024. http://dx.doi.org/10.4018/978-1-6684-7366-5.ch012.

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Success in the air freight sector is closely tied to the ability to consolidate freight shipments. The essence of the load planning algorithm consists of a predetermined arrangement of cargo containers relative to the cargo compartment, considering the general aircraft limitations and the priority of the cargo. The visualized load planning model enables flight planning staff to predict additional re-loading on other sections of the route. The model serves as the basis for a rule-based expert system in order to prevent containers from being overloaded at intermediate routes. The results aimed at increasing the efficiency and safety of ground handling services as well as intensification of use of the air company's fleet.
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Sahun, Yelyzaveta Serhiyivna. "Perspective Directions of Artificial Intelligence Systems in Aircraft Load Optimization Process." In Handbook of Research on Artificial Intelligence Applications in the Aviation and Aerospace Industries. IGI Global, 2020. http://dx.doi.org/10.4018/978-1-7998-1415-3.ch018.

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The chapter represents an overview of different approaches towards loading process and load planning. The algorithm and specificities of the current cargo loading process force the scientists to search for new methods of optimizing due to the time, weight, and size constraints of the cargo aircraft and consequently to cut the costs for aircraft load planning and handling procedures. These methods are based on different approaches: mix-integer linear programs, three-dimensional bin packing, knapsack loading algorithms, tabu-search approach, rule-based approach, and heuristics. The perspective direction of aircraft loading process improvement is a combination of multicriteria optimization method and heuristic approach using the expert system.
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"ANN-Based Short-Term Load Forecasting." In EHT Transmission Performance Evaluation. IGI Global, 2018. http://dx.doi.org/10.4018/978-1-5225-4941-3.ch006.

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Load forecasting is a very crucial issue for the operational planning of electrical power systems. In the sixth chapter, it is formulated that a reliable power network along with load prediction models is essential for uninterrupted supply of electrical energy to the consumers. The Back-Propagation ANN algorithm is applied to forecast the load of the power system. Based on the load forecasted power components, transmission lines and sub-stations are augmented for improved reliability in a province.
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Zhang, Zhen, Jiawei Xiao, and Wenwei Zhang. "A*-Based Path Generation Algorithm for Multi-Optimized Fixed-Wing UAVs." In Advances in Transdisciplinary Engineering. IOS Press, 2024. https://doi.org/10.3233/atde241231.

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In recent years, unmanned aerial vehicle (UAV) technology has made remarkable progress in many fields, especially in the path planning of fixed-wing UAVs. In the face of complex task scenarios, fixed UAVs need to consider various scenarios, generate conforms to aircraft performance, and make autonomous decision-making to evade and standby flight routes to meet the needs of load adaptation and performance guarantee. Especially for some specific load unmanned aerial vehicles (UAVs), the flight path planning is in advance before launch, so the ground stage of route planning is the key. This paper puts forward A kind based on A* heuristic search algorithm of the optimum path planning method, through the Alpha - Beta pruning to accelerate the search process, using Douglas-Peucker curve smoking loose to reduce cost, time and space combined with spline interpolation and polynomial fitting rounds of optimization, Finally, the critical routes with the ability to evade, wait and attack are generated. The experimental results show that the algorithm achieves 4.5% optimization in the path length, and the smoothness of the curve is improved by 36.71%. It has the planning ability to hover and wait in the mission area, effectively improving the path generation’s smoothness, effectiveness, and refinement. It also reduces the route length, showing good anti-data noise and long path planning ability.
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Ye, Gaoxiang, Jie Yang, Feifan Shao, et al. "Resource Allocation Schemes for Distribution Networks Under Source-Load Uncertainty." In Frontiers in Artificial Intelligence and Applications. IOS Press, 2024. http://dx.doi.org/10.3233/faia241117.

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A multi-objective optimal allocation model is established by constructing probabilistic models of photovoltaic, wind turbine output, load and electric vehicle charging power. The model takes into account the economy of investment, network stability and social and environmental benefits. In order to solve this model, an improved multi-objective particle swarm algorithm is proposed, and the probabilistic trend calculation is carried out using the semi-invariant method to verify the constraints. The efficiency and effectiveness of the proposed method are verified through simulation, especially in terms of computation time and planning efficiency.
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Pantazis Dimitrios, Rodriguez Adrian Ayastuy, Conway Paul P., and West Andrew A. "An Application of Autoregressive Hidden Markov Models for Identifying Machine Operations." In Advances in Transdisciplinary Engineering. IOS Press, 2016. https://doi.org/10.3233/978-1-61499-668-2-193.

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Due to increasing energy costs there is a need for accurate management and planning of shop floor machine processes. This would entail identifying the different operation modes of production machines. The goal for industry is to provide energy monitors for all machines in factories. In addition, where they have been deployed, analysis is limited to aggregating data for subsequent processing later. In this paper, an Autoregressive Hidden Markov Model (ARHMM)-based algorithm is introduced, which can determine the operation mode of the machine in real-time and find direct application in intrusive load monitoring cases. Compared with other load monitoring techniques, such as transient analysis, no prior knowledge of the system to be monitored is required.
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"Operating Schedule of a Combined Energy Network System." In Advances in Environmental Engineering and Green Technologies. IGI Global, 2014. http://dx.doi.org/10.4018/978-1-4666-5796-0.ch001.

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This chapter consists of two sections, ‘Operating Schedule of a Combined Energy Network System with Fuel Cell’ and ‘Fuel Cell Network System Considering Reduction in Fuel Cell Capacity Using Load Leveling and Heat Release Loss’. The chromosome model showing system operation pattern is applied to GA (genetic algorithm), and the method of optimization operation planning of energy system is developed in the 1st section. In the case study, the operation planning was performed for the energy system using the energy demand pattern of the individual residence of Sapporo, Japan. Reduction in fuel cell capacity linked to a fuel cell network system is considered in the 2nd section. Such an energy network is analyzed assuming connection of individual houses, a hospital, a hotel, a convenience store, an office building, and a factory.
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Conference papers on the topic "Load planning algorithm"

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Potyagaylo, Svetlana, Anton Cooper, and Omri Rand. "Slung Load Transportation by Multiple Rotary-Wing Vehicles." In Vertical Flight Society 73rd Annual Forum & Technology Display. The Vertical Flight Society, 2017. http://dx.doi.org/10.4050/f-0073-2017-12197.

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This paper focuses on the problem of payload transportation by a flock of rotary-wing vehicles. The flock includes several aerial vehicles and a cable-suspended load that has to be transported from an initial position to a goal position in an a priori known environment. The development of several novel techniques including a detailed modeling of the quadrotor dynamics, a control architecture, and a dedicated motion planning algorithm based on a modified Rapidly-Explored Random Tree (RRT) method for the flock are presented in this paper. The proposed system modules were checked in different clu
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Cao, Liang, Jinling Wu, Xuan Wang, et al. "Coordinated Planning and Control Strategy of Source-Load-Storage in Distribution Network Based on Improved HHO-GSA Algorithm." In 2024 6th International Conference on Energy Systems and Electrical Power (ICESEP). IEEE, 2024. http://dx.doi.org/10.1109/icesep62218.2024.10651745.

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Choi, Inyoung, Seonghoon Kim, and Jihwan P. Choi. "A Simplified Algorithm for Online Satellite Network Slice Planning with Trade-Off Between Load-Balancing and Minimum-Hop Routing." In 2024 15th International Conference on Information and Communication Technology Convergence (ICTC). IEEE, 2024. https://doi.org/10.1109/ictc62082.2024.10827308.

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Chen, Chao-Rong, Wen-Ta Tsai, Hua-Yi Chen, Ching-Ying Lee, Chun-Ju Chen, and Hong-Wei Lan. "Optimal load shedding planning with genetic algorithm." In 2011 IEEE Industry Applications Society Annual Meeting. IEEE, 2011. http://dx.doi.org/10.1109/ias.2011.6074299.

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Kim, Joo H., Jingzhou Yang, and Karim Abdel-Malek. "Load-Effective Dynamic Motion Planning for Redundant Manipulators." In ASME 2007 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. ASMEDC, 2007. http://dx.doi.org/10.1115/detc2007-35393.

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The robotic motion planning criteria has evolved from kinematics to dynamics in recent years. Many research achievements have been made in dynamic motion planning, but the externally applied loads are usually limited to the gravity force. Due to the increasing demand for generic tasks, the motion should be generated for various functions such as pulling, pushing, twisting, and bending. In this presentation, a comprehensive form of equations of motion, which includes the general external loads applied at any points of the system, is derived and implemented. An optimization-based algorithm is th
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Abedi, Mohsen, and Risto Wichman. "Planning and optimization of Cellular Networks Using Load-based Voronoi Algorithm." In 2018 52nd Asilomar Conference on Signals, Systems, and Computers. IEEE, 2018. http://dx.doi.org/10.1109/acssc.2018.8645189.

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Behera, Santi, Manish Tripathy, and Jitendriya Kumar Satapathy. "Optimal reactive power planning for load margin increase with BFO algorithm." In 2015 Annual IEEE India Conference (INDICON). IEEE, 2015. http://dx.doi.org/10.1109/indicon.2015.7443671.

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Arulraj, R., and N. Kumarappan. "Hybrid WIPSO-GSA Algorithm Based Optimal DG and Capacitor Planning Considering Different Load Types and Load Levels." In 2018 IEEE Congress on Evolutionary Computation (CEC). IEEE, 2018. http://dx.doi.org/10.1109/cec.2018.8477650.

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Bokah, Abdihakim, and Alireza Maheri. "An Algorithm for Load Planning of Renewable Powered Machinery with Variable Operation Time." In 2021 6th International Symposium on Environment-Friendly Energies and Applications (EFEA). IEEE, 2021. http://dx.doi.org/10.1109/efea49713.2021.9406273.

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Skolthanarat, Siriya, Udom Lewlomphaisarl, and Kanokvate Tungpimolrut. "Short-term load forecasting algorithm and optimization in smart grid operations and planning." In 2014 IEEE Conference on Technologies for Sustainability (SusTech). IEEE, 2014. http://dx.doi.org/10.1109/sustech.2014.7046238.

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Reports on the topic "Load planning algorithm"

1

Boardman, Beth Leigh. Sampling-Based Motion Planning Algorithms for Replanning and Spatial Load Balancing. Office of Scientific and Technical Information (OSTI), 2017. http://dx.doi.org/10.2172/1400115.

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