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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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Metaheuristics for Combinatorial Optimization
2021It is well known, and it is easy to prove that any problem can be formulated and tackled as an optimization problem since solving it means basically making deci- sions. Every day each of us continually makes decisions during own daily activities, from simple and automatic ones (e.g., choose a food or dress to wear), to more challenging and complex ones
Greco S +3 more
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A survey on optimization metaheuristics
Information Sciences, 2013zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Boussaid, Ilhem +2 more
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METAHEURISTIC OPTIMIZATION OF ACOUSTIC INVERSE PROBLEMS
Journal of Computational Acoustics, 2011Swift solving of geoacoustic inverse problems strongly depends on the application of a global optimization scheme. Given a particular inverse problem, this work aims to answer the questions how to select an appropriate metaheuristic search strategy, and how to configure it for optimal performance.
van Leijen, A.V. +2 more
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Metaheuristics for Portfolio Optimization
2017Portfolio optimization refers to allocating an amount of investors’ wealth to different assets in order to satisfy the investors’ preferences for return and risk. We address the portfolio optimization problem with real-world constraints, where traditional optimization methods fail to efficiently find an optimal or near-optional solution.
Sarah El-Bizri, Nashat Mansour
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Metaheuristic Optimization in Structural Engineering
2015Metaheuristic search methods have been extensively used for optimization of the structures over the past two decades. Genetic algorithms (GA), ant colony optimization (ACO), particle swarm optimization (PSO), harmony search (HS), big bang-big crunch (BB-BC), artificial bee colony algorithm (ABC) and teaching–learning-based optimization (TLBO) are the ...
Değertekin, S. Ö., Geem, Zong Woo
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Metaheuristic Optimization Programs
2018There are optimization processes of industrial interest that involve functions that present a large number of local solutions, and therefore it is very difficult to determine the optimal solution using deterministic optimization techniques. For example, consider the case shown in Fig.
José María Ponce-Ortega +1 more
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Gradient-based optimizer: A new metaheuristic optimization algorithm
Information Sciences, 2020zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Iman Ahmadianfar +2 more
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Metaheuristics in combinatorial optimization
ACM Computing Surveys, 2003The field of metaheuristics for the application to combinatorial optimization problems is a rapidly growing field of research. This is due to the importance of combinatorial optimization problems for the scientific as well as the industrial world. We give a survey of the nowadays most important metaheuristics from a conceptual point of view. We outline
Blum C., Roli A.
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Metaheuristics for Optimization Problems
2018An introduction to metaheuristics for optimization problems is presented in this chapter. In Sect. 3.1 a classification of metaheuristics is put forward. The metaheuristics Differential Evolution (DE); Particle Collision Algorithm (PCA); Ant Colony Optimization (ACO) in its version for continuous problems; and Particle Swarm Optimization (PSO) are ...
Lídice Camps Echevarría +3 more
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