Results 31 to 40 of about 6,937 (265)
PHH: Policy-Based Hyper-Heuristic With Reinforcement Learning
IEEE Access, 2023 Hyper-heuristics have a high level of generality and adaptability, allowing them to effectively solve a wide range of complex optimization problems.
Orachun Udomkasemsub +2 more
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Problem Solving in Crowd Management Using Heuristic Approach
IEEE Access, 2022 There are many problems that procedural algorithms can solve efficiently. However, these algorithms are sometimes too slow to abide by the time available for performing the solution; other times, it is impossible to get a solution using procedural ...
Ali M. Al-Shaery +4 more
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Scheduling Mandatory-Optional Real-Time Tasks in Homogeneous Multi-Core Systems with Energy Constraints Using Bio-Inspired Meta-Heuristics [PDF]
Journal of Universal Computer Science, 2019 In this paper we present meta-heuristics to solve the energy aware reward based scheduling of real-time tasks with mandatory and optional parts in homogeneous multi-core processors. The problem is NP-Hard.
Matias Micheletto +2 more
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Proceedings of the Conference on Production Systems and Logistics, 2023 Reconfigurable manufacturing systems (RMS) are capable of adjusting their operating point to the requirements of current customer demand with high degrees of freedom.
Behrendt, Sebastian +6 more
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Scheduling for Additive Manufacturing: a literature review
Gestão & Produção, 2022 : Advancements in production technologies and materials have facilitated the use of additive manufacturing (AM) (i.e., 3D printing) in the large-scale production of finished products with high level of customization, simplification of the factory floor ...
Gabriela Dall’Agnol +2 more
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An Ant Colony based Hyper-Heuristic Approach for the Set Covering Problem
Advances in Distributed Computing and Artificial Intelligence Journal, 2015 The Set Covering Problem (SCP) is a NP-hard combinatorial optimization problem that is challenging for meta-heuristic algorithms. In the optimization literature, several approaches using meta-heuristics have been developed to tackle the SCP and the ...
Alexandre Silvestre FERREIRA +2 more
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Meta-Heuristics: An Overview [PDF]
, 1996 Meta-heuristics are the most recent development in approximate search methods for solving complex optimization problems, that arise in business, commerce, engineering, industry, and many other areas. A meta-heuristic guides a subordinate heuristic using concepts derived from artificial intelligence, biological, mathematical, natural and physical ...
Ibrahim H. Osman, James P. Kelly
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Hybrid meta-heuristics for combinatorial optimization [PDF]
Constraints, 2015 Combinatorial optimization problems arise, in many forms, in various aspects of everyday life. Nowadays, a lot of services are driven by optimization algorithms, enabling us to make the best use of the available resources while guaranteeing a level of service. Examples of such services are public transportation, goods delivery, university time-tabling,
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Significance relations for the benchmarking of meta-heuristic algorithms [PDF]
2013 13th International Conference on Intellient Systems Design and Applications, 2013 The experimental analysis of meta-heuristic algorithm performance is usually based on comparing average performance metric values over a set of algorithm instances. When algorithms getting tight in performance gains, the additional consideration of significance of a metric improvement comes into play.
Mario Köppen, Kei Ohnishi
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Solving the Mask Data Preparation Scheduling Problem Using Meta-Heuristics
IEEE Access, 2019 Mask data preparation (MDP) is a part of the mask data process for fabricating semiconductors, and its importance has commonly been neglected. This paper proposes an integer linear programming model and two meta-heuristics, a genetic algorithm (GA) and ...
Kuo-Ching Ying +4 more
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