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EMO
2005
Springer
68views Optimization» more  EMO 2005»
15 years 3 months ago
Multi-objective Optimization of Problems with Epistemic Uncertainty
Abstract. Multi-objective evolutionary algorithms (MOEAs) have proven to be a powerful tool for global optimization purposes of deterministic problem functions. Yet, in many real-w...
Philipp Limbourg
73
Voted
EMO
2003
Springer
81views Optimization» more  EMO 2003»
15 years 2 months ago
Solving Hierarchical Optimization Problems Using MOEAs
Abstract. In this paper, we propose an approach for solving hierarchical multi-objective optimization problems (MOPs). In realistic MOPs, two main challenges have to be considered:...
Christian Haubelt, Sanaz Mostaghim, Jürgen Te...
80
Voted
TJS
2002
122views more  TJS 2002»
14 years 9 months ago
Optimal BSR Solutions to Several Convex Polygon Problems
Abstract. This paper focuses on BSR (Broadcasting with Selective Reduction) implementation of algorithms solving basic convex polygon problems. More precisely, constant time soluti...
Jean Frédéric Myoupo, David Sem&eacu...
ASIAN
1999
Springer
186views Algorithms» more  ASIAN 1999»
15 years 2 months ago
Ant Colony Optimization for the Ship Berthing Problem
Abstract. Ant Colony Optimization (ACO) is a paradigm that employs a set of cooperating agents to solve functions or obtain good solutions for combinatorial optimization problems. ...
Chia Jim Tong, Hoong Chuin Lau, Andrew Lim
CEC
2011
IEEE
13 years 9 months ago
Oppositional biogeography-based optimization for combinatorial problems
Abstract—In this paper, we propose a framework for employing opposition-based learning to assist evolutionary algorithms in solving discrete and combinatorial optimization proble...
Mehmet Ergezer, Dan Simon