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Antonella Nardin and Fabio D?Andreagiovanni
Electric scooter sharing mobility services have recently spread in major cities all around the world. However, the bad parking behavior of users has become a major source of issues, provoking accidents and compromising urban decorum of public areas. Redu...
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Claudia Cavallaro, Carolina Crespi, Vincenzo Cutello, Mario Pavone and Francesco Zito
This paper introduces an agent-based model grounded in the ACO algorithm to investigate the impact of partitioning ant colonies on algorithmic performance. The exploration focuses on understanding the roles of group size and number within a multi-objecti...
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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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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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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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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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Zheping Yan, Weidong Liu, Wen Xing and Enrique Herrera-Viedma
How an autonomous underwater vehicle (AUV) performs fully automated task allocation and achieves satisfactory mission planning effects during the search for potential threats deployed in an underwater space is the focus of the paper. First, the task assi...
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Shuo-Tsung Chen, Tsung-Hsien Wu, Ren-Jie Ye, Liang-Ching Lee, Wen-Yu Huang, Yi-Hong Lin and Bo-Yao Wang
Recommended travel itinerary planning is an important issue in travel platforms or travel systems. Most research focuses on minimizing the time spent traveling between attractions or the cost of attractions. This study makes four contributions to recomme...
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