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Parameter Tuning of Metaheuristics Using Metaheuristics
Advanced Science Letters, 2013Ant colony optimization; Genetic algorithms; Metaheuristics; Optimization; Parameter setting; Scatter ...
Broderick Crawford +4 more
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Metaheuristics: A Canadian Perspective
INFOR: Information Systems and Operational Research, 2008Metaheuristics are generic search strategies that can be adapted to solve complex problems. This paper describes in simple terms the most popular metaheuristics for combinatorial optimization problems. It also emphasizes the main contributions of the Canadian research community in the development and application of metaheuristics.
Michel Gendreau, Jean-Yves Potvin
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2008
Decision support systems (DSSs) provide modern solution techniques that help the decision maker to find the best solution to a problem. These embedded solution techniques include and combine, but are not limited to, simulation, exact optimization methods, and heuristics.
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Decision support systems (DSSs) provide modern solution techniques that help the decision maker to find the best solution to a problem. These embedded solution techniques include and combine, but are not limited to, simulation, exact optimization methods, and heuristics.
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The 'Blackboard Pattern' for Metaheuristics
Proceedings of the Companion Publication of the 2015 Annual Conference on Genetic and Evolutionary Computation, 2015We describe the 'Blackboard' design pattern for metaheuristics which allows multiple agents to combine their expertise opportunistically to contribute towards a solution. Features of the Blackboard pattern may include heterogeneity of solution representations (e.g.
Kevin Carrie Graham +2 more
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Metaheuristics for Dynamic Optimization
2013This book is an updated effort in summarizing the trending topics and new hot research lines in solving dynamic problems using metaheuristics. An analysis of the present state in solving complex problems quickly draws a clear picture: problems that change in time, having noise and uncertainties in their definition are becoming very important. The tools
Alba, Enrique +2 more
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Decomposing Metaheuristic Operations
2013Non-exhaustive local search methods are fundamental tools in applied branches of computing such as operations research, and in other applications of optimisation. These problems have proven stubbornly resistant to attempts to find generic meta-heuristic toolkits that are both expressive and computationally efficient for the large problem spaces ...
Richard Senington, David Duke
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DESICOM as Metaheuristic Search
2020Decomposition into Simple Components (DESICOM) is a constrained matrix factorization method to decompose asymmetric square data matrices and represent them as combinations of very sparse basis matrices as well as dense asymmetric affinity matrices. When cast as a least squares problem, the process of finding the factor matrices needs special attention ...
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Metaheuristics for graph bisection
Proceedings of the 11th Annual conference on Genetic and evolutionary computation, 2009This paper compares several metaheuristics on the balanced graph bisection problem and identifies their relative performance on structured test graphs. For this purpose, a Simple implementation of a graph Bisection Iterated Local Search algorithm (SBILS) is introduced. Its results are compared to the well-known Genetic Bisection Algorithm, to the state-
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