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Evolutionary algorithms in theory and practice
TLDR
In this work, the author compares the three most prominent representatives of evolutionary algorithms: genetic algorithms, evolution strategies, and evolutionary programming within a unified framework, thereby clarifying the similarities and differences of these methods.About:
The article was published on 1996-01-01 and is currently open access. It has received 2679 citations till now. The article focuses on the topics: Evolutionary music & Evolutionary programming.read more
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A new multi-objective optimization method for master production scheduling problems based on genetic algorithm
TL;DR: In this article, the authors present the development and use of genetic algorithm (GA) to MPS problems, something that does not seem to have been done so far, and describe the multi-objective fitness function used, the set of possible individual selection techniques, and the adjustment values for the crossover and mutation operators.
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Parallel scalable hardware implementation of asynchronous discrete particle swarm optimization
TL;DR: A novel hardware framework of particle swarm optimization (PSO) for various kinds of discrete optimization problems based on the system-on-a-programmable-chip (SOPC) concept, with results indicating a speed-up of up to 98 times over the software implementation in the elapsed computation time.
How Do Pedestrians find their Way? Results of an experimental study with students compared to simulation results
Angelika Kneidl,André Borrmann +1 more
TL;DR: To map large-scale orientation of pedestrians, a basic model was extended by a navigation graph and this model was used as a basis for different routing algorithms, thus modeling different types of pedestrians.
A Distributed Genetic Algorithm with Migration for the Design of Composite Laminate Structures.
TL;DR: The performance of the dGA in terms of cost and reliability is studied and compared to an sGA baseline, using two types of composite laminate design problems.
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3D UAV trajectory planning using evolutionary algorithms: A comparison study
Mehri Bagherian,A. Alos +1 more
TL;DR: This paper focuses on the three dimensional flight path planning for an unmanned aerial vehicle (UAV) on a low altitude terrain following terrain avoidance mission, and two heuristic algorithms are proposed: genetic and particle swarm algorithms.