Combining Metaheuristics and Exact Algorithms in Combinatorial Optimization: A Survey and Classification

By Jakob Puchinger, Günther R. Raidl. International Work-Conference on the Interplay Between Natural and Artificial Computation, 2005

374 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Computer Networks and Communications, Industrial and Manufacturing Engineering

View Paper: https://www.semanticscholar.org/paper/e8bcdad3691a4014d14b69d49e902adcab0cc38d

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Artificial Intelligence

1. Ahmet Cosar
2. Tansel Dökeroğlu
3. Tayfun Kucukyilmaz
4. Ender Sevinç

In Computer Networks and Communications

1. Ahmet Cosar
2. Tansel Dökeroğlu
3. Tayfun Kucukyilmaz
4. Ender Sevinç

In Industrial and Manufacturing Engineering

1. Ahmet Cosar
2. Tansel Dökeroğlu
3. Tayfun Kucukyilmaz
4. Ender Sevinç

Citations in the corpus

• A survey on new generation metaheuristic algorithms (2019, background): “Puchinger and Raidl (2005) discuss different state-of-the-art techniques to combine metaheuristics with brute-force algorithms to optimize combinatorial problems.”
• Metaheuristic research: a comprehensive survey (2018, neutral): “Different approaches have been introduced in this regard (Jourdan et al. 2009; Puchinger and Raidl 2005), which are mainly aimed at achieving better and efficient solutions early in the iterations.”