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GECCO
2004
Springer
101views Optimization» more  GECCO 2004»
15 years 7 months ago
A Novel Multi-objective Orthogonal Simulated Annealing Algorithm for Solving Multi-objective Optimization Problems with a Large
In this paper, a novel multi-objective orthogonal simulated annealing algorithm MOOSA using a generalized Pareto-based scale-independent fitness function and multi-objective intell...
Li-Sun Shu, Shinn-Jang Ho, Shinn-Ying Ho, Jian-Hun...
CEC
2010
IEEE
15 years 3 months ago
Many-objective Distinct Candidates Optimization using Differential Evolution on centrifugal pump design problems
Many-objective problems are difficult to solve using conventional multi-objective evolutionary algorithms (MOEAs) as these algorithms rely primarily on Pareto ranking to guide the ...
Peter Dueholm Justesen, Rasmus K. Ursem
ICRA
2010
IEEE
119views Robotics» more  ICRA 2010»
15 years 1 months ago
Solving the continuous time multiagent patrol problem
— This paper compares two algorithms to solve a multiagent patrol problem with uncertain durations. The first algorithm is reactive and allows adaptive and robust behavior, whil...
Jean-Samuel Marier, Camille Besse, Brahim Chaib-dr...
WSC
2008
15 years 4 months ago
Discrete stochastic optimization using linear interpolation
We consider discrete stochastic optimization problems where the objective function can only be estimated by a simulation oracle; the oracle is defined only at the discrete points....
Honggang Wang, Bruce W. Schmeiser
JUCS
2008
159views more  JUCS 2008»
15 years 2 months ago
Two Step Swarm Intelligence to Solve the Feature Selection Problem
: In this paper we propose a new approach to Swarm Intelligence called Two-Step Swarm Intelligence. The basic idea is to split the heuristic search performed by agents into two sta...
Yudel Gómez, Rafael Bello, Amilkar Puris, M...