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127
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GECCO
2009
Springer
131views Optimization» more  GECCO 2009»
15 years 7 months ago
Rapid prototyping using evolutionary approaches: part 1
In this paper we describe a multi-objective problem solving approach, simultaneously minimizing average surface roughness Ra and build Time T, for object manufacturing by Rapid Pr...
Nikhil Padhye, Subodh Kalia
99
Voted
CEC
2007
IEEE
15 years 8 months ago
On performance metrics and particle swarm methods for dynamic multiobjective optimization problems
— This paper describes two performance measures for measuring an EMO (Evolutionary Multiobjective Optimization) algorithm’s ability to track a time-varying Paretofront in a dyn...
Xiaodong Li, Jürgen Branke, Michael Kirley
GECCO
2006
Springer
132views Optimization» more  GECCO 2006»
15 years 6 months ago
A new multi-objective evolutionary algorithm for solving high complex multi-objective problems
Kangshun Li, Xuezhi Yue, Lishan Kang, Zhangxin Che...
EC
2000
96views ECommerce» more  EC 2000»
15 years 2 months ago
Multiobjective Evolutionary Algorithms: Analyzing the State-of-the-Art
Solving optimization problems with multiple (often conflicting) objectives is, generally, a very difficult goal. Evolutionary algorithms (EAs) were initially extended and applied ...
David A. van Veldhuizen, Gary B. Lamont
GECCO
2003
Springer
15 years 7 months ago
Use of Multiobjective Optimization Concepts to Handle Constraints in Single-Objective Optimization
Abstract. In this paper, we propose a new constraint-handling technique for evolutionary algorithms which is based on multiobjective optimization concepts. The approach uses Pareto...
Arturo Hernández Aguirre, Salvador Botello ...