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Artykuły w czasopismach na temat „Multi-Task Optimisation”

Autor: Grafiati

Data publikacji: 31 sierpnia 2024

Data aktualizacji: 19 lipca 2025

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1

Pearce, Michael, and Juergen Branke. "Continuous multi-task Bayesian Optimisation with correlation." European Journal of Operational Research 270, no. 3 (2018): 1074–85. http://dx.doi.org/10.1016/j.ejor.2018.03.017.

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Li, Feng, Lin Zhang, T. W. Liao, and Yongkui Liu. "Multi-objective optimisation of multi-task scheduling in cloud manufacturing." International Journal of Production Research 57, no. 12 (2018): 3847–63. http://dx.doi.org/10.1080/00207543.2018.1538579.

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Panchu K., Padmanabhan, M. Rajmohan, R. Sundar, and R. Baskaran. "Multi-objective Optimisation of Multi-robot Task Allocation with Precedence Constraints." Defence Science Journal 68, no. 2 (2018): 175. http://dx.doi.org/10.14429/dsj.68.11187.

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Efficacy of the multi-robot systems depends on proper sequencing and optimal allocation of robots to the tasks. Focuses on deciding the optimal allocation of set-of-robots to a set-of-tasks with precedence constraints considering multiple objectives. Taguchi’s design of experiments based parameter tuned genetic algorithm (GA) is developed for generalised task allocation of single-task robots to multi-robot tasks. The developed methodology is tested for 16 scenarios by varying the number of robots and number of tasks. The scenarios were tested in a simulated environment with a maximum of 20 rob

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Bellotti, Renato, Romana Boiger, and Andreas Adelmann. "Fast, Efficient and Flexible Particle Accelerator Optimisation Using Densely Connected and Invertible Neural Networks." Information 12, no. 9 (2021): 351. http://dx.doi.org/10.3390/info12090351.

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Particle accelerators are enabling tools for scientific exploration and discovery in various disciplines. However, finding optimised operation points for these complex machines is a challenging task due to the large number of parameters involved and the underlying non-linear dynamics. Here, we introduce two families of data-driven surrogate models, based on deep and invertible neural networks, that can replace the expensive physics computer models. These models are employed in multi-objective optimisations to find Pareto optimal operation points for two fundamentally different types of particl

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Cvetkovski, Goga, and Lidija Petkovska. "Design Improvement of Permanent Magnet Motor Using Single- and Multi-Objective Approaches." Power Electronics and Drives 9, no. 1 (2024): 34–49. http://dx.doi.org/10.2478/pead-2024-0003.

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Abstract Optimisation, or optimal design, has become a fundamental aspect of engineering across various domains, including power devices, power systems, and industrial systems. Engineers and academics have been actively involved in optimising these systems to achieve better performance, efficiency, and cost-effectiveness. Optimising electrical machines, including permanent magnet motors, is a complex task. It often involves solving intricate problems with various parameters and constraints. Engineers use different optimisation methods to tackle these challenges. Depending on the specific requi

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Jawade, Prashant Balkrishna, and S. Ramachandram. "Task scheduling in multi-cloud environment via improved optimisation theory." International Journal of Wireless and Mobile Computing 27, no. 1 (2024): 64–77. http://dx.doi.org/10.1504/ijwmc.2024.139671.

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Trianni, Vito, and Manuel López-Ibáñez. "Advantages of Task-Specific Multi-Objective Optimisation in Evolutionary Robotics." PLOS ONE 10, no. 8 (2015): e0136406. http://dx.doi.org/10.1371/journal.pone.0136406.

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Ramachandram, S., and Prashant Balkrishna Jawade. "Task scheduling in multi-cloud environment via improved optimisation theory." International Journal of Wireless and Mobile Computing 27, no. 1 (2024): 64–77. http://dx.doi.org/10.1504/ijwmc.2024.10064647.

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Lisowski, Józef. "Multi-Criteria Optimisation of Multi-Stage Positional Game of Vessels." Polish Maritime Research 27, no. 1 (2020): 46–52. http://dx.doi.org/10.2478/pomr-2020-0005.

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AbstractThe paper presents a mathematical model of a positional game of the safe control of a vessel in collision situations at sea, containing a description of control, state variables and state constraints as well as sets of acceptable ship strategies, as a multi-criteria optimisation task. The three possible tasks of multi-criteria optimisation were formulated in the form of non-cooperative and cooperative multi-stage positional games as well as optimal non-game controls. The multi-criteria control algorithms corresponding to these tasks were subjected to computer simulation in Matlab/Simul

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10

Goddanti, N. S. S. L. Venkata Jwala, Pooja Ponakampalli, Shiny Sharon Neela, Reashma Sulthana Shaik, and V. Suresh Chintalapudi. "An OptiAssign-PSO based optimisation for multi-objective multi-level multi-task scheduling in cloud computing environment." i-manager’s Journal on Cloud Computing 11, no. 1 (2024): 1. http://dx.doi.org/10.26634/jcc.11.1.20484.

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Cloud computing is a prominent and evolving distributed computing paradigm that provides users with on-demand services through a network of diverse autonomous systems with flexible computational structures. The significance of task scheduling becomes evident, serving as a vital component to elevating cloud computing's overall performance. Streamlining cost-effective execution and optimizing resource utilization is a key objective, given the NP-hard nature of the task scheduling problem. Although numerous meta-heuristic techniques have been explored to address task allocation challenges, ample

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Faroqi, Hamed, and Mohammad saadi Mesgari. "Performance Comparison between the Multi-Colony and Multi-Pheromone ACO Algorithms for Solving the Multi-objective Routing Problem in a Public Transportation Network." Journal of Navigation 69, no. 1 (2015): 197–210. http://dx.doi.org/10.1017/s0373463315000594.

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Routing in a multimodal urban public transportation network, according to the user's preferences, can be considered as a multi-objective optimisation problem. Solving this problem is a complicated task due to the different and incompatible objective functions, various modes in the network, and the large size of the network. In this research, two optimisation algorithms are considered for solving this problem. The multi-colony and multi-pheromone Ant Colony Optimisation (ACO) algorithms are two different modes of the Multi-Objective ACO (MOACO) algorithm. Moreover, according to the acquired inf

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12

Robinson, G. M., and A. J. Keane. "A case for multi-level optimisation in aeronautical design." Aeronautical Journal 103, no. 1028 (1999): 481–85. http://dx.doi.org/10.1017/s0001924000064435.

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Abstract This paper discusses how the inevitable limitations of computing power available to designers has restricted adoption of optimisation as an essential design tool. It is argued that this situation will continue until optimisation algorithms are developed which utilise the range of available analysis methods in a manner more like human designers. The concept of multi-level algorithms is introduced and a case made for their adoption as the way forward. The issues to be addressed in the development of multi-level algorithms are highlighted. The paper goes on to discuss a system developed

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Trianni, Vito, and Manuel López-Ibáñez. "Correction: Advantages of Task-Specific Multi-Objective Optimisation in Evolutionary Robotics." PLOS ONE 10, no. 10 (2015): e0140056. http://dx.doi.org/10.1371/journal.pone.0140056.

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Kandasamy, Kirthevasan, Gautam Dasarathy, Junier Oliva, Jeff Schneider, and Barnabás Póczos. "Multi-fidelity Gaussian Process Bandit Optimisation." Journal of Artificial Intelligence Research 66 (September 15, 2019): 151–96. http://dx.doi.org/10.1613/jair.1.11288.

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In many scientific and engineering applications, we are tasked with the maximisation of an expensive to evaluate black box function f. Traditional settings for this problem assume just the availability of this single function. However, in many cases, cheap approximations to f may be obtainable. For example, the expensive real world behaviour of a robot can be approximated by a cheap computer simulation. We can use these approximations to eliminate low function value regions cheaply and use the expensive evaluations of f in a small but promising region and speedily identify the optimum. We form

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Dong, Xueshi, Wenyong Dong, and Yongle Cai. "Ant colony optimisation for coloured travelling salesman problem by multi-task learning." IET Intelligent Transport Systems 12, no. 8 (2018): 774–82. http://dx.doi.org/10.1049/iet-its.2016.0282.

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Liu, Weining, Bo Liu, Dihua Sun, Yiming Li, and Gang Ma. "Study on multi-task oriented services composition and optimisation with the ‘Multi-Composition for Each Task’ pattern in cloud manufacturing systems." International Journal of Computer Integrated Manufacturing 26, no. 8 (2013): 786–805. http://dx.doi.org/10.1080/0951192x.2013.766939.

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Mısır, Oğuz. "Advanced Multi-Robot Path Planning Based on Grey Wolf and Teaching-Learning Based Optimisation." Akıllı Ulaşım Sistemleri ve Uygulamaları Dergisi 8, no. 1 (2025): 204–22. https://doi.org/10.51513/jitsa.1608792.

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Multi-robots stand out for their flexibility, scalability, and robustness in complex tasks by collaborating. Rather than a single robot undertaking a task, many robots can perform one or more tasks, which increases the task efficiency. Mobile robots require path planning to reach the targeted locations while working in areas such as service, logistics, agriculture, and production. This situation is also valid for multi-robots. In this study, an advanced multi-robot path planning method adapted to the path planning of multi-robots is proposed by combining the advantageous aspects of the Grey Wo

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18

Sarathambekai, S., and K. Umamaheswari. "Task scheduling using multi-objective hamming discrete particle swarm optimisation in distributed systems." International Journal of Swarm Intelligence 2, no. 2/3/4 (2016): 100. http://dx.doi.org/10.1504/ijsi.2016.081132.

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Sarathambekai, S., and K. Umamaheswari. "Task scheduling using multi-objective hamming discrete particle swarm optimisation in distributed systems." International Journal of Swarm Intelligence 2, no. 2/3/4 (2016): 100. http://dx.doi.org/10.1504/ijsi.2016.10002174.

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Karczewski, Artur, and Janusz Kozak. "A Generative Approach to Hull Design for a Small Watercraft." Polish Maritime Research 30, no. 1 (2023): 4–12. http://dx.doi.org/10.2478/pomr-2023-0001.

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Abstract In the field of ocean engineering, the task of spatial hull modelling is one of the most complicated problems in ship design. This study presents a procedure applied as a generative approach to the design problems for the hull geometry of small vessels using elements of concurrent design with multi-criteria optimisation processes. Based upon widely available commercial software, an algorithm for the mathematical formulation of the boundary conditions, the data flow during processing and formulae for the optimisation processes are developed. As an example of the application of this nov

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Nagalakshmi, Bantupalli, and Sumathy Subramanian. "An efficient multi-objective task scheduling in edge computing using adaptive honey badger optimisation." International Journal of Web Engineering and Technology 19, no. 2 (2024): 110–26. http://dx.doi.org/10.1504/ijwet.2024.139866.

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Bamohabbat Chafjiri, Sadegh, Phil Legg, Michail-Antisthenis Tsompanas, and Jun Hong. "Leveraging activation and optimisation layers as dynamic strategies in the multi-task fuzzing scheme." Computer Standards & Interfaces 94 (August 2025): 104011. https://doi.org/10.1016/j.csi.2025.104011.

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Benkhelifa, Elhadj, Ashutosh Tiwari, and Mohamed Abdel-Maguid. "Advanced Design Optimisation by Means of Multiobjective Evolutionary Algorithms: The Case of Two Real World Applications." Key Engineering Materials 572 (September 2013): 589–92. http://dx.doi.org/10.4028/www.scientific.net/kem.572.589.

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The Design Optimisation (DO) of Complex Systems is often a multidisciplinary task and involves multiple conflicting objectives and design constraints, where conventional methods cannot solve efficiently. This paper presents Advanced DO by Means of Evolutional Algorithms in two Real World Applications Electronics and Micro-Electro-Mechanical-Systems (MEMS). The former is presented in the context of multi-objective evolutionary synthesis and optimisation of analogue systems. As for the latter, DO of MEMS bio-mimetically is a very novel area of research, Which addresses the compelling change in t

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Bonisoli, Elvio, Francesco Di Monaco, Stefano Tornincasa, Fabio Freschi, Luca Giaccone, and Maurizio Repetto. "Multi-physics optimisation of an energy harvester device for automotive application." COMPEL: The International Journal for Computation and Mathematics in Electrical and Electronic Engineering 33, no. 3 (2014): 846–55. http://dx.doi.org/10.1108/compel-10-2012-0208.

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Purpose – Supplying remote wireless sensors is not an easy task if the site where the device is located is not easily accessible. In order to obtain direct measurements of the road-vehicle interactions, sensors must be placed inside the tyre environment thus a power supply must be available for their working there without any wire connection with the car main power. The paper aims to discuss these issues. Design/methodology/approach – An electro-mechanical energy harvester has thus been developed for supplying an automotive wireless sensor of pressure, temperature and acceleration to be placed

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Wang, Fu, Yanghao Zhang, Xiangyu Yin, et al. "A Black-Box Evaluation Framework for Semantic Robustness in Bird’s Eye View Detection." Proceedings of the AAAI Conference on Artificial Intelligence 39, no. 7 (2025): 7637–45. https://doi.org/10.1609/aaai.v39i7.32822.

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Camera-based Bird's Eye View (BEV) perception models receive increasing attention for their crucial role in autonomous driving, a domain where concerns about the robustness and reliability of deep learning have been raised. While only a few works have investigated the effects of randomly generated semantic perturbations, aka natural corruptions, on the multi-view BEV detection task, we develop a black-box robustness evaluation framework that adversarially optimises three common semantic perturbations: geometric transformation, colour shifting, and motion blur, to deceive BEV models, serving as

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Chander, Satish, P. Vijaya, and Praveen Dhyani. "ADOFL: Multi-Kernel-Based Adaptive Directive Operative Fractional Lion Optimisation Algorithm for Data Clustering." Journal of Intelligent Systems 27, no. 3 (2018): 317–29. http://dx.doi.org/10.1515/jisys-2016-0175.

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Abstract The progress of databases in fields such as medical, business, education, marketing, etc., is colossal because of the developments in information technology. Knowledge discovery from such concealed bulk databases is a tedious task. For this, data mining is one of the promising solutions and clustering is one of its applications. The clustering process groups the data objects related to each other in a similar cluster and diverse objects in another cluster. The literature presents many clustering algorithms for data clustering. Optimisation-based clustering algorithm is one of the rece

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Guze, Sambor, Tomasz Neumann, and Przemysław Wilczyński. "Multi-Criteria Optimisation of Liquid Cargo Transport According to Linguistic Approach to the Route Selection Task." Polish Maritime Research 24, s1 (2017): 89–96. http://dx.doi.org/10.1515/pomr-2017-0026.

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AbstractThe main aim of the paper is to present the possibility of use of the multi-criteria optimization method Analytical Hierarchy Process (AHP) to liquid cargo transportation by sea. Finding the optimal solution is not simple. There are many factors influencing the shipping process. In the case of liquid cargo, the most important thing is the safety of the crew, ship, and environment. Therefore, the Mathematical Theory of Evidence is introduced and used to determine the optimal path in terms of time and safety of transport. Moreover, the details of liquid cargo transport process are descri

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López Ruiz, José L., Ángeles Verdejo Espinosa, Alicia Montoro Lendínez, and Macarena Espinilla Estévez. "OBLEA: A New Methodology to Optimise Bluetooth Low Energy Anchors in Multi-occupancy Location Systems." JUCS - Journal of Universal Computer Science 29, no. 6 (2023): 627–46. http://dx.doi.org/10.3897/jucs.96878.

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Nowadays, it is becoming increasingly important to understand the multiple configuration factors of BLE anchors in indoor location systems. This task becomes particularly crucial in the context of activity recognition in multi-occupancy smart environments. Knowing the impact of the configuration of BLE anchors in an indoor location system allows us to distinguish the interactions performed by each inhabitant in a smart environment according to their proximity to each sensor. This paper proposes a new methodology, OBLEA, that determines the optimisation of Bluetooth Low Energy (BLE) anchors in

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López, Ruiz José L., Espinosa Ángeles Verdejo, Lendínez Alicia Montoro, and Estévez Macarena Espinilla. "OBLEA: A New Methodology to Optimise Bluetooth Low Energy Anchors in Multi-occupancy Location Systems." JUCS - Journal of Universal Computer Science 29, no. (6) (2023): 627–46. https://doi.org/10.3897/jucs.96878.

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Nowadays, it is becoming increasingly important to understand the multiple configuration factors of BLE anchors in indoor location systems. This task becomes particularly crucial in the context of activity recognition in multi-occupancy smart environments. Knowing the impact of the configuration of BLE anchors in an indoor location system allows us to distinguish the interactions performed by each inhabitant in a smart environment according to their proximity to each sensor. This paper proposes a new methodology, OBLEA, that determines the optimisation of Bluetooth Low Energy (BLE) anchors in

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Zheng, ShiYu, and Xiang Jing Yu. "An Overview Study of Multi-sensor Fusion for Map Building and Localization." Advances in Research 26, no. 1 (2025): 247–56. https://doi.org/10.9734/air/2025/v26i11250.

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This paper reviews the application of multi-sensor fusion in simultaneous localisation and map construction (SLAM) technology. With the development of robotics, autonomous driving and virtual reality, there is an increasing demand for precise localisation and map construction.SLAM technology has emerged to solve the problem of autonomous robot localisation and map construction in unknown environments. However, single-sensor SLAM systems have limitations, such as limited sensing capability and susceptibility to noise interference. Multi-sensor fusion SLAM significantly improves the performance

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Minaeva, Yu V. "ATHEMATICAL MODEL FOR THE OPTIMISATION OF HIERARCHICAL MULTI-LEVEL PRODUCTION SYSTEMS." Herald of Dagestan State Technical University. Technical Sciences 45, no. 2 (2018): 140–48. http://dx.doi.org/10.21822/2073-6185-2018-45-2-140-148.

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Objectives The aim of the study is to develop a mathematical model for the complex solution of various problems in designing and reconstructing the technological system of a production workshop of a machine-building enterprise.Methods Complex system theory and an aggregative decomposition approach are used as the methodological basis for modelling complex hierarchical productions, making it possible to represent a complex system in the form of a set of interconnected subsystems.Results A mathematical model designed for a complex solution of problems associated with the formation of an optimal

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Zhang, Qinglei, Ning Li, Jianguo Duan, Jiyun Qin, and Ying Zhou. "Resource Scheduling Optimisation Study Considering Both Supply and Demand Sides of Services under Cloud Manufacturing." Systems 12, no. 4 (2024): 133. http://dx.doi.org/10.3390/systems12040133.

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In cloud manufacturing environments, the scheduling of multi-user manufacturing tasks often fails to consider the impact of service supply on resource allocation. This study addresses this gap by proposing a bi-objective multi-user multi-task scheduling model aimed at simultaneously minimising workload and maximising customer satisfaction. To accurately capture customer satisfaction, a novel comprehensive rating index is introduced, integrating the actual completion cost, time, and processing quality against customer expectations. Furthermore, vehicle constraints are incorporated into the mode

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Albowarab, Mustafa Hasan, Nurul Azma Zakaria, and Zaheera Zainal Abidin. "Directionally-Enhanced Binary Multi-Objective Particle Swarm Optimisation for Load Balancing in Software Defined Networks." Sensors 21, no. 10 (2021): 3356. http://dx.doi.org/10.3390/s21103356.

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Various aspects of task execution load balancing of Internet of Things (IoTs) networks can be optimised using intelligent algorithms provided by software-defined networking (SDN). These load balancing aspects include makespan, energy consumption, and execution cost. While past studies have evaluated load balancing from one or two aspects, none has explored the possibility of simultaneously optimising all aspects, namely, reliability, energy, cost, and execution time. For the purposes of load balancing, implementing multi-objective optimisation (MOO) based on meta-heuristic searching algorithms

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Bawane, Madhuri N., and K. M. Bhurchandi. "Multi-objective particle swarm optimisation for mental task classification using hybrid features and hierarchical neural network classifier." International Journal of Biomedical Engineering and Technology 32, no. 2 (2020): 177. http://dx.doi.org/10.1504/ijbet.2020.10027366.

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Bawane, Madhuri N., and K. M. Bhurchandi. "Multi-objective particle swarm optimisation for mental task classification using hybrid features and hierarchical neural network classifier." International Journal of Biomedical Engineering and Technology 32, no. 2 (2020): 177. http://dx.doi.org/10.1504/ijbet.2020.105653.

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Stanko, Petro, Olena Ohremchuk, Daria Salamatina, and Daria Sverdlova. "TASK SCHEDULING OPTIMISATION OF DISTRIBUTED REAL-TIME COMPUTING SYSTEMS." Science-based technologies 60, no. 4 (2024): 386–93. http://dx.doi.org/10.18372/2310-5461.60.18267.

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Distributed computing structures for production and special purposes represent the resources of soft or hard real-time systems. The problem of task planning is to determine the optimal distribution according to the generalized criterion of system utility. The article discusses the methods of building a schedule, based on the theory of planning. It is shown that the most effective step in this process is the optimisation of the activity of the enterprises or organizations at all levels - economic, technical, informational, etc., under the conditions of natural limitations on time resources. Sin

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Dharani Pragada, Venkata Aditya, Akanistha Banerjee, and Srinivasan Venkataraman. "OPTIMISATION OF NAVAL SHIP COMPARTMENT LAYOUT DESIGN USING GENETIC ALGORITHM." Proceedings of the Design Society 1 (July 27, 2021): 2339–48. http://dx.doi.org/10.1017/pds.2021.495.

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AbstractAn efficient general arrangement is a cornerstone of a good ship design. A big part of the whole general arrangement process is finding an optimized compartment layout. This task is especially tricky since the multiple needs are often conflicting, and it becomes a serious challenge for the ship designers. To aid the ship designers, improved and reliable statistical and computation methods have come to the fore. Genetic algorithms are one of the most widely used methods. Islier's algorithm for the multi-facility layout problem and an improved genetic algorithm for the ship layout design

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Zhang, Mingfang, Raluca Chitic, and Sander M. Bohté. "Energy optimization induces predictive-coding properties in a multi-compartment spiking neural network model." PLOS Computational Biology 21, no. 6 (2025): e1013112. https://doi.org/10.1371/journal.pcbi.1013112.

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Predictive coding is a prominent theoretical framework for understanding hierarchical sensory processing in the brain, yet how it could be implemented in networks of cortical neurons is still unclear. While most existing studies have taken a hand-wiring approach to creating microcircuits that match experimental results, recent work in rate-based artificial neural networks revealed that suitable cortical connectivity might result from self-organisation given some fundamental computational principle, such as energy efficiency. As no corresponding approach has studied this in more plausible netwo

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Agyemang, Brighter, Fenghui Ren, and Jun Yan. "Proactive Agent Behaviour in Dynamic Distributed Constraint Optimisation Problems." Information 15, no. 5 (2024): 255. http://dx.doi.org/10.3390/info15050255.

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In multi-agent systems, the Dynamic Distributed Constraint Optimisation Problem (D-DCOP) framework is pivotal, allowing for the decomposition of global objectives into agent constraints. Proactive agent behaviour is crucial in such systems, enabling agents to anticipate future changes and adapt accordingly. Existing approaches, like Proactive Dynamic DCOP (PD-DCOP) algorithms, often necessitate a predefined environment model. We address the problem of enabling proactive agent behaviour in D-DCOPs where the dynamics model of the environment is unknown. Specifically, we propose an approach where

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Hameed, Khurram, Douglas Chai, and Alexander Rassau. "A Sample Weight and AdaBoost CNN-Based Coarse to Fine Classification of Fruit and Vegetables at a Supermarket Self-Checkout." Applied Sciences 10, no. 23 (2020): 8667. http://dx.doi.org/10.3390/app10238667.

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The physical features of fruit and vegetables make the task of vision-based classification of fruit and vegetables challenging. The classification of fruit and vegetables at a supermarket self-checkout poses even more challenges due to variable lighting conditions and human factors arising from customer interactions with the system along with the challenges associated with the colour, texture, shape, and size of a fruit or vegetable. Considering this complex application, we have proposed a progressive coarse to fine classification technique to classify fruit and vegetables at supermarket check

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Elsedimy, Elsayed, and Fahad Algarni. "MOTS‐ACO: An improved ant colony optimiser for multi‐objective task scheduling optimisation problem in cloud data centres." IET Networks 11, no. 2 (2022): 43–57. http://dx.doi.org/10.1049/ntw2.12033.

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Saravana Balaji, B., Gomathi B, and Karthikeyan Krishnasamy. "Epsilon-Fuzzy Dominance Sort Based Composite Discrete Artificial Bee Colony optimisation for Multi-Objective Cloud Task Scheduling Problem." International Journal of Business Intelligence and Data Mining 12, no. 3/4 (2017): 1. http://dx.doi.org/10.1504/ijbidm.2017.10004803.

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Gomathi, B., Karthikeyan Krishnasamy, and B. Saravana Balaji. "Epsilon-fuzzy dominance sort-based composite discrete artificial bee colony optimisation for multi-objective cloud task scheduling problem." International Journal of Business Intelligence and Data Mining 13, no. 1/2/3 (2018): 247. http://dx.doi.org/10.1504/ijbidm.2018.088435.

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Veneri, Giacomo, Francesca Rosini, Pamela Federighi, Antonio Federico, and Alessandra Rufa. "Evaluating gaze control on a multi-target sequencing task: The distribution of fixations is evidence of exploration optimisation." Computers in Biology and Medicine 42, no. 2 (2012): 235–44. http://dx.doi.org/10.1016/j.compbiomed.2011.11.013.

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Lomazzi, L., F. Cadini, M. Giglio, et al. "Integrated multi-objective optimisation of the support structure of heliostats in concentrated solar power plants using a genetic algorithm." IOP Conference Series: Materials Science and Engineering 1214, no. 1 (2022): 012027. http://dx.doi.org/10.1088/1757-899x/1214/1/012027.

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Abstract The optimisation of the support structure of heliostats in concentrating solar power plants is a fundamental task aimed at attempting to reduce the high levelised cost of energy (LCOE) of current configurations. In this work, an integrated multi-objective optimisation framework is presented, which relies on the combination of a lean and fast structural model with a genetic algorithm to simultaneously minimise both the overall mass of the support structure and the mean angle of rotation of the mirror surface, which directly affects the optical efficiency of the component. A particular

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SUN, YUEXIN, and YU CHEN. "Fast textile pattern generation combining MRF-based and Gram-based methods." Industria Textila 74, no. 04 (2023): 439–45. http://dx.doi.org/10.35530/it.074.04.202254.

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Textile pattern design is a tedious and challenging task for designers. This paper proposes a fast textile pattern generation algorithm that combines MRF-based and Gram-based methods. First, the reconstruction method based on image optimisation is determined after analysing the specific requirements of textile pattern design. The pre-trained VGG19 is selected as the style feature extraction neural network. Then, we compare the generation results of various combinations of style loss functions and propose a multi-resolution image optimisation method. Finally, the smoothing loss and colour histo

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Andreu Casas, Enric, ALBERTO GARCIA VILLORIA, and RAFAEL PASTOR MORENO. "SOLVING THE MULTI-MANNED ASSEMBLY LINE BALANCING PROBLEM WITH DEPENDENT TASK TIMES BY MEANS OF EMPIRICALLY ADJUSTED GREEDY HEURISTICS (EAGH)." DYNA MANAGEMENT 11, no. 1 (2023): [9P.]. http://dx.doi.org/10.6036/mn10905.

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ABSTRACT: Multi-manned assembly lines are widely used in manufacturing industries that process a high-volume of large-sized workpieces. At each workstation there are multiple workers simultaneously performing different tasks with the possibility of interfering with each other, leading to an increase in the processing task times. This paper studies this type of problem: the multi-manned assembly line balancing problem with dependent task times (MALBP-DTT). As discussed in recent literature, the HEUR_PART procedure presents the best behaviour for solving MALBP-DTT. In this paper, HEUR_PART is im

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Garus, Jerzy, and Bogdan Żak. "The practical aspects of implementation of the thrust allocation procedure for a multi-propulsor underwater robot." Polish Hyperbaric Research 65, no. 4 (2018): 39–48. http://dx.doi.org/10.2478/phr-2018-0022.

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Abstract This article addresses the practical aspects of the synthesis of an automatic control system for the thrust allocation strategy in the propulsion system of an unmanned underwater vehicle. The vehicle under consideration is a robot submarine equipped with a multi-propulsion system providing four degrees of freedom of movement. The power distribution algorithms are based on limited optimisation methods that allow the determination, on the basis of generalised torques and forces, of how much thrust is required to be produced by individual propulsors. Considering the issue of power distri

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Cheng Seong, Khor. "A Model-Based Optimisation Approach for Process Synthesis of Olefins from Petroleum with Application to the Malaysian Petrochemical Industry." ASM Science Journal 12 (December 30, 2019): 1–15. http://dx.doi.org/10.32802/asmscj.2019.393.

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The shale gas revolution has rekindled interest in olefins production due to the abundance of ethane as a raw material resource. However, the main technology still revolves around the cost-intensive distillation operation. Hence this work aims to investigate the economic optimisation of olefins synthesis from petroleum in the light of recent developments. A model-based approach is applied to determine the optimal sequencing of separation and reaction processes for a multi-component hydrocarbon mixture feed to produce mainly ethylene and propylene. a mixed-integer linear program (MILP) is formu

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Nurhafizah Anual, Siti, Mohd Faisal Ibrahim, Nurhana Ibrahim, et al. "GA-based Optimisation of a LiDAR Feedback Autonomous Mobile Robot Navigation System." Bulletin of Electrical Engineering and Informatics 7, no. 3 (2018): 433–41. http://dx.doi.org/10.11591/eei.v7i3.1275.

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Autonomous mobile robots require an efficient navigation system in order to navigate from one location to another location fast and safe without hitting static or dynamic obstacles. A light-detection-and-ranging (LiDAR) based autonomous robot navigation is a multi-component navigation system consists of various parameters to be configured. With such structure and sometimes involving conflicting parameters, the process of determining the best configuration for the system is a non-trivial task. This work presents an optimisation method using Genetic algorithm (GA) to configure such navigation sy

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