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Performance Measures of Metaheuristic Algorithms
2015Generally speaking, it is not fully understood why and how metaheuristic algorithms work very well under what conditions. It is the intention of this paper to clarify the performance characteristics of some of popular algorithms depending on the fitness landscape of specific problems. This study shows the performance of each considered algorithm on the
Joong Hoon Kim +3 more
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A Metaheuristic Algorithm for the Probabilistic Orienteering Problem
Proceedings of the 2019 2nd International Conference on Machine Learning and Machine Intelligence, 2019The Probabilistic Orienteering Problem (POP) is a variant of the orienteering problem where customers are available with a certain probability. In a previous work, we approximated its objective function value by using a Monte Carlo Sampling method. A heuristic speed-up criterion is considered in the objective function evaluator.
Xiaochen Chou +2 more
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A Metaheuristic Algorithm for Ship Weather Routing
Operations Research Forum, 2022zbMATH Open Web Interface contents unavailable due to conflicting licenses.
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Metaheuristic Optimization Algorithms
2021In this introductory chapter, specific state-of-the-art metaheuristic optimization algorithms are outlined. The presented algorithms belong to the broad trajectory-based and population-based categories, and they are particularly selected as they constitute the building blocks of algorithm portfolios presented in the forthcoming chapters.
Dimitris Souravlias +3 more
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A Metaheuristic Algorithm for Hiding Sensitive Itemsets
2018In this paper, we first present a multi-objective algorithm for hiding the sensitive information with transaction deletion based on the NSGAII framework. The proposed can efficiently sort the non-dominated solutions and find the set of Pareto results for later process.
Jerry Chun-Wei Lin +4 more
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Metaheuristic Clustering Algorithms
2020Metaheuristic algorithms are well-known optimization tools which have been used in many applications including those in data mining. In particular, these algorithms are well suited for solving nonconvex clustering problems since they are able to find global solutions whereas the traditional clustering algorithms such as k-means can only guarantee ...
Adil Bagirov +2 more
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Batch metaheuristic: a migration-free framework for metaheuristic algorithms
Evolutionary Intelligence, 2023Deepika Kaushik +2 more
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A Racing Algorithm for Configuring Metaheuristics.
2002info:eu-repo/semantics ...
Birattari, Mauro +3 more
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