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A Study of Composite Heuristic Algorithms

Journal of the Operational Research Society, 1987
When faced with a difficult combinatorial problem whose optimization may be prohibitively expensive, researchers frequently turn to the stuy of fast heuristic algorithms in an effort to guarantee near-optimal results. An important aspect in the evaluation of such an algorithm is the determination of its worst-case behaviour, relative to an optimization
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Hybrid heuristic algorithms for Set Covering

Computers & Operations Research, 1998
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
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A heuristic for blocking flow algorithms

European Journal of Operational Research, 1996
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
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Worst-Case Analysis of Heuristic Algorithms

Management Science, 1980
The increased focus on heuristics for the approximate solution of integer programs has led to more sophisticated analysis methods for studying their performance. This paper is concerned with the worst-case approach to the analysis of heuristic performance.
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Heuristic Algorithms

2000
H. A. Eiselt, C.-L. Sandblom
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Artificial rabbits optimization: A new bio-inspired meta-heuristic algorithm for solving engineering optimization problems

Engineering Applications of Artificial Intelligence, 2022
Liying Wang   +2 more
exaly  

Heuristic Network Search Algorithm

1991
Many AI applications require a search for a best (or shortest) path through a net-work. Applications for network searches include routing problems (such as aircraft or sales route planning and terrain traversal for robotic vehicles).
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Reptile Search Algorithm (RSA): A nature-inspired meta-heuristic optimizer

Expert Systems With Applications, 2022
Laith Mohammad Abualigah   +2 more
exaly  

Unicycle heuristic optimization algorithm

This paper proposes a heuristic optimization algorithm based on the dynamics and balance characteristics of a unicycle. This algorithm simulates the unicyclist's behavior in maintaining dynamic balance, adjusting lean angle, controlling speed, and fine-tuning the center of gravity during movement, thereby mapping the optimization problem into a dynamic
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