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Metaheuristic
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=== Local search vs. global search === One approach is to characterize the type of search strategy.<ref name="blum03metaheuristics" /> One type of search strategy is an improvement on simple local search algorithms. A well known local search algorithm is the [[hill climbing]] method which is used to find local optimums. However, hill climbing does not guarantee finding global optimum solutions. Many metaheuristic ideas were proposed to improve local search heuristic in order to find better solutions. Such metaheuristics include [[simulated annealing]], [[tabu search]], [[iterated local search]], [[Variable Neighborhood Search|variable neighborhood search]], and [[Greedy randomized adaptive search procedure|GRASP]].<ref name="blum03metaheuristics" /> These metaheuristics can both be classified as local search-based or global search metaheuristics. Other global search metaheuristic that are not local search-based are usually [[Population model (evolutionary algorithm)|population-based]] metaheuristics. Such metaheuristics include [[ant colony optimization]], [[evolutionary computation]] such as [[genetic algorithm]] or [[Evolution strategy|evolution strategies]], [[particle swarm optimization]], [[rider optimization algorithm]]<ref>{{cite journal |last1=D |first1=Binu |title=RideNN: A New Rider Optimization Algorithm-Based Neural Network for Fault Diagnosis in Analog Circuits |journal=IEEE Transactions on Instrumentation and Measurement |year=2019 |volume=68 |issue=1 |pages=2β26 |doi=10.1109/TIM.2018.2836058 |bibcode=2019ITIM...68....2B |s2cid=54459927 |url=https://ieeexplore.ieee.org/document/8370147}}</ref> and bacterial foraging algorithm.<ref name=":0">{{Cite journal |last1=Pang |first1=Shinsiong |last2=Chen |first2=Mu-Chen |date=2023-06-01 |title=Optimize railway crew scheduling by using modified bacterial foraging algorithm |url=https://www.sciencedirect.com/science/article/pii/S0360835223002425 |journal=Computers & Industrial Engineering |language=en |volume=180 |pages=109218 |doi=10.1016/j.cie.2023.109218 |s2cid=257990456 |issn=0360-8352}}</ref>
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