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Gleice Kelly Barbosa Souza, Samara Oliveira Silva Santos, André Luiz Carvalho Ottoni, Marcos Santos Oliveira, Daniela Carine Ramires Oliveira and Erivelton Geraldo Nepomuceno
Reinforcement learning is an important technique in various fields, particularly in automated machine learning for reinforcement learning (AutoRL). The integration of transfer learning (TL) with AutoRL in combinatorial optimization is an area that requir...
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Giorgio Lazzarinetti, Riccardo Dondi, Sara Manzoni and Italo Zoppis
Solving combinatorial problems on complex networks represents a primary issue which, on a large scale, requires the use of heuristics and approximate algorithms. Recently, neural methods have been proposed in this context to find feasible solutions for r...
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Shu-Shun Liu, Putri Utami, Agung Budiwirawan, Muhammad Faizal Ardhiansyah Arifin and Fernanda Sarwatatwadhika Perdana
The preservation and maintenance of ancient buildings, particularly heritage buildings, is a complex process that requires careful consideration of several aspects, including maintenance plans and budget availability. An effective long-term maintenance p...
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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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Shenquan Huang, Ya-Chih Tsai and Fuh-Der Chou
This paper considers the single-machine problem with job release times and flexible preventive maintenance activities to minimize total weighted tardiness, a complicated scheduling problem for which many algorithms have been proposed in the literature. H...
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Bahram Alidaee, Haibo Wang and Lutfu S. Sua
Quadratic unconstrained binary optimization (QUBO) is a classic NP-hard problem with an enormous number of applications. Local search strategy (LSS) is one of the most fundamental algorithmic concepts and has been successfully applied to a wide range of ...
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Fei Tian, Chen Yang, Erfeng Zhang, Dehua Sun, Weidong Shi and Yonghua Chen
Optimizing hydraulic machinery is a critical research area within the field of fluid mechanics, aiming to enhance product design efficiency and improve performance while reducing development time. The application of intelligent algorithms and combinatori...
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Aphisak Witthayapraphakorn, Sasarose Jaijit and Peerayuth Charnsethikul
A novel approach was developed that combined LP-based row generation with optimization-based sorting to tackle computational challenges posed by budget allocation problems with combinatorial constraints. The proposed approach dynamically generated constr...
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Magnus Daniel Kallinger, José Ignacio Rapha, Pau Trubat Casal and José Luis Domínguez-García
Electrical grid layout optimization should consider the placements of turbines and substations and include effects such as wake losses, power losses in cables, availability of different cable types, reliability-based power losses and operational/decommis...
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Toufik Mzili, Ilyass Mzili, Mohammed Essaid Riffi and Gaurav Dhiman
This paper presents a new hybrid algorithm that combines genetic algorithms (GAs) and the optimizing spotted hyena algorithm (SHOA) to solve the production shop scheduling problem. The proposed GA-SHOA algorithm incorporates genetic operators, such as un...
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