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EVOW
2004
Springer
13 years 11 months ago
Constructing Dynamic Optimization Test Problems Using the Multi-objective Optimization Concept
Abstract. Dynamic optimization using evolutionary algorithms is receiving increasing interests. However, typical test functions for comparing the performance of various dynamic opt...
Yaochu Jin, Bernhard Sendhoff
HPCC
2007
Springer
13 years 9 months ago
A New Method for Multi-objective TDMA Scheduling in Wireless Sensor Networks Using Pareto-Based PSO and Fuzzy Comprehensive Judg
In wireless sensor networks with many-to-one transmission mode, a multi-objective TDMA (Time Division Multiple Access) scheduling model is presented, which concerns about the packe...
Tao Wang, Zhiming Wu, Jianlin Mao
GECCO
2008
Springer
199views Optimization» more  GECCO 2008»
13 years 6 months ago
Analysis of multi-objective evolutionary algorithms to optimize dynamic data types in embedded systems
New multimedia embedded applications are increasingly dynamic, and rely on Dynamically-allocated Data Types (DDTs) to store their data. The optimization of DDTs for each target em...
José Ignacio Hidalgo, José L. Risco-...
GECCO
2007
Springer
182views Optimization» more  GECCO 2007»
13 years 12 months ago
An analysis of the effects of population structure on scalable multiobjective optimization problems
Multiobjective evolutionary algorithms (MOEA) are an effective tool for solving search and optimization problems containing several incommensurable and possibly conflicting objec...
Michael Kirley, Robert L. Stewart
GECCO
2006
Springer
127views Optimization» more  GECCO 2006»
13 years 9 months ago
Multiobjective genetic algorithms for multiscaling excited state direct dynamics in photochemistry
This paper studies the effectiveness of multiobjective genetic and evolutionary algorithms in multiscaling excited state direct dynamics in photochemistry via rapid reparameteriza...
Kumara Sastry, D. D. Johnson, Alexis L. Thompson, ...