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Concept

heuristics (combinatorial optimization)

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221

Publications

16.4K

Citations

456

Authors

246

Institutions

About

Heuristics (combinatorial optimization) is a class of algorithmic approaches and problem-solving techniques used to find approximate, high-quality solutions to complex combinatorial optimization problems. These problems involve selecting the best combination or permutation from a finite set of options, often under constraints, with the goal of optimizing an objective function. Heuristics are particularly valuable when finding an exact optimal solution is computationally intractable or impractical due to problem size or complexity, such as in NP-hard problems. They operate by trading off guaranteed optimality for computational speed and efficiency, aiming to achieve good, near-optimal solutions within reasonable timeframes. This approach is widely applied in domains like network optimization, resource allocation challenges in media marketing, and various computational tasks relevant to behavioral finance, where efficient, effective decision-making support is required for large-scale or time-sensitive problems.

Top Authors

Rankings shown are based on concept H-Index.

GG

Max Planck Institute for Human Development

AG

Max Planck Institute for Research on Collective Goods

PM

Max Planck Institute for Human Development

PB

University of Georgia

University of Nottingham

Top Institutions

Rankings shown are based on concept H-Index.

Max Planck Society

Munich, Germany

Pittsburgh, United States

University of Warwick

Coventry, United Kingdom

University of Mannheim

Mannheim, Germany