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Evangelos Filippou, Spyridon Kilimtzidis, Athanasios Kotzakolios and Vassilis Kostopoulos
The pursuit of more efficient transport has led engineers to develop a wide variety of aircraft configurations with the aim of reducing fuel consumption and emissions. However, these innovative designs introduce significant aeroelastic couplings that can...
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Michalis Mavrovouniotis, Maria N. Anastasiadou and Diofantos Hadjimitsis
Ant colony optimization (ACO) has proven its adaptation capabilities on optimization problems with dynamic environments. In this work, the dynamic traveling salesman problem (DTSP) is used as the base problem to generate dynamic test cases. Two types of ...
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Nikola Ivkovic, Robert Kudelic and Marin Golub
Ant colony optimization (ACO) is a well-known class of swarm intelligence algorithms suitable for solving many NP-hard problems. An important component of such algorithms is a record of pheromone trails that reflect colonies? experiences with previously ...
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Dennis Delali Kwesi Wayo, Sonny Irawan, Alfrendo Satyanaga and Jong Kim
Data-driven models with some evolutionary optimization algorithms, such as particle swarm optimization (PSO) and ant colony optimization (ACO) for hydraulic fracturing of shale reservoirs, have in recent times been validated as one of the best-performing...
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Shilpa Gite, Shruti Patil, Deepak Dharrao, Madhuri Yadav, Sneha Basak, Arundarasi Rajendran and Ketan Kotecha
Feature selection and feature extraction have always been of utmost importance owing to their capability to remove redundant and irrelevant features, reduce the vector space size, control the computational time, and improve performance for more accurate ...
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Guoqiang Zhang, Irfan Ahmed Khan, Amil Daraz, Abdul Basit and Muhammad Irshad Khan
In seaports, low-carbon energy systems and energy efficiency have become increasingly important as a result of the evolution of environmental and climate change challenges. In order to ensure the continued success of seaports, technological advancements ...
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Sílvia de Castro Pereira, Eduardo J. Solteiro Pires and Paulo B. de Moura Oliveira
A new algorithm based on the ant colony optimization (ACO) method for the multiple traveling salesman problem (mTSP) is presented and defined as ACO-BmTSP. This paper addresses the problem of solving the mTSP while considering several salesmen and keepin...
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Pavel V. Matrenin
Planning tasks are important in construction, manufacturing, logistics, and education. At the same time, scheduling problems belong to the class of NP-hard optimization problems. Ant colony algorithm optimization is one of the most common swarm intellige...
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Shruti Bharadwaj, Rakesh Dubey, Md Iltaf Zafar, Rashid Faridi, Debashish Jena and Susham Biswas
Urban planning, noise propagation modelling, viewshed analysis, etc., require determination of routes or supply lines for propagation. A point-to-point routing algorithm is required to determine the best routes for the propagation of noise levels from so...
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Xiaojun Li, Weibing Wang, Ganghui Liu, Runze Li and Fei Li
In greenhouse nurseries, one of the important tasks of the automatic transplanter is replanting missing or bad seedling holes with healthy seedlings. This requires the transplanter to spend significant time moving between the supply trays and target tray...
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