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AI
2010
Springer
15 years 3 months ago
Elicitation strategies for soft constraint problems with missing preferences: Properties, algorithms and experimental studies
We consider soft constraint problems where some of the preferences may be unspecified. This models, for example, settings where agents are distributed and have privacy issues, or ...
Mirco Gelain, Maria Silvia Pini, Francesca Rossi, ...
122
Voted
GECCO
2007
Springer
185views Optimization» more  GECCO 2007»
15 years 9 months ago
SNDL-MOEA: stored non-domination level MOEA
There exist a number of high-performance Multi-Objective Evolutionary Algorithms (MOEAs) for solving MultiObjective Optimization (MOO) problems; two of the best are NSGA-II and -M...
Matt D. Johnson, Daniel R. Tauritz, Ralph W. Wilke...
123
Voted
GECCO
2008
Springer
161views Optimization» more  GECCO 2008»
15 years 4 months ago
A new quantum behaved particle swarm optimization
This paper presents a variant of Quantum behaved Particle Swarm Optimization (QPSO) named Q-QPSO for solving global optimization problems. The Q-QPSO algorithm is based on the cha...
Millie Pant, Radha Thangaraj, Ajith Abraham
109
Voted
GECCO
2006
Springer
123views Optimization» more  GECCO 2006»
15 years 7 months ago
Real-time construction of aircraft landing schedules using an evolutionary algorithm
This poster investigates the use of Evolutionary Algorithms (EAs) to optimise solutions to the Dynamic Aircraft Landing Problem (DALP). The approach adopted here uses an EA to evo...
Neil Urquhart
140
Voted
TNN
1998
132views more  TNN 1998»
15 years 3 months ago
Synthesis of fault-tolerant feedforward neural networks using minimax optimization
—In this paper we examine a technique by which fault tolerance can be embedded into a feedforward network leading to a network tolerant to the loss of a node and its associated w...
Dipti Deodhare, M. Vidyasagar, S. Sathiya Keerthi