Exact(1)
The use of optimization metaheuristics such as Genetic Algorithms, Particle Swarm and Ant Colonies Optimization has been successful in ICFMO.
Similar(59)
This chapter surveys the use of metaheuristics for simulation optimization, focusing on work bridging the current gap between the practical use of such methods and research, and points out some promising directions for research in this area.
An effective proposal to this problem is to solve it in the domain of ant colony optimization metaheuristics.
Optimization-based process design can be accomplished by the formulation of superstructures and the use of metaheuristics as well as deterministic optimization.
The proposed SRTC makes use of the intelligent metaheuristic optimization search even under tight timeliness constraints.
In terms of optimization, various metaheuristics have been proposed to the optimal chiller loading problem.
It extends the "white-box" ParadisEO framework for metaheuristics applied to the resolution of mono/multi-objective Combinatorial Optimization Problems requiring both the use of advanced optimization methods and the exploitation of large-scale parallel and distributed environments.
The optimization is performed by the use of several metaheuristic algorithms, including PSO, FA, WOA, and CSA.
Then we present a solution strategy based on global optimization metaheuristics.
This optimization method is based on the use of metaheuristic techniques.
A whole research branch in truss optimization is also dedicated to the use of metaheuristic methods, with for example the use of genetic algorithms by Rajan [8] and Deb and Gulati [9], a multi-population evolutionary method by Wu and Tseng [10], or an harmony search algorithm by Lee and Geem [11].
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