Zobrazeno 1 - 10
of 114
pro vyhledávání: '"Liefooghe, Arnaud"'
The hardness of the Unconstrained Binary Quadratic Program (UBQP) problem is due its rugged landscape. Various algorithms have been proposed for UBQP, including the Landscape Smoothing Iterated Local Search (LSILS). Different from other UBQP algorith
Externí odkaz:
http://arxiv.org/abs/2407.19676
Combinatorial optimization problem (COP) is difficult to solve because of the massive number of local optimal solutions in his solution space. Various methods have been put forward to smooth the solution space of COPs, including homotopic convex (HC)
Externí odkaz:
http://arxiv.org/abs/2401.03237
Autor:
Ayodele, Mayowa, Allmendinger, Richard, López-Ibáñez, Manuel, Liefooghe, Arnaud, Parizy, Matthieu
Multi-objective optimisation problems involve finding solutions with varying trade-offs between multiple and often conflicting objectives. Ising machines are physical devices that aim to find the absolute or approximate ground states of an Ising mode
Externí odkaz:
http://arxiv.org/abs/2305.11648
Publikováno v:
In European Journal of Operational Research 16 November 2024 319(1):89-101
The difficulty of solving a multi-objective optimization problem is impacted by the number of objectives to be optimized. The presence of many objectives typically introduces a number of challenges that affect the choice/design of optimization algori
Externí odkaz:
http://arxiv.org/abs/2106.03275
Autor:
Dreo, Johann, Liefooghe, Arnaud, Verel, Sébastien, Schoenauer, Marc, Merelo, Juan J., Quemy, Alexandre, Bouvier, Benjamin, Gmys, Jan
The success of metaheuristic optimization methods has led to the development of a large variety of algorithm paradigms. However, no algorithm clearly dominates all its competitors on all problems. Instead, the underlying variety of landscapes of opti
Externí odkaz:
http://arxiv.org/abs/2105.00420
Publikováno v:
In Expert Systems With Applications 5 March 2025 263
This paper intends to understand and to improve the working principle of decomposition-based multi-objective evolutionary algorithms. We review the design of the well-established Moea/d framework to support the smooth integration of different strateg
Externí odkaz:
http://arxiv.org/abs/2004.06961