An architecture for exploring large design spaces
AAAI '98/IAAI '98 Proceedings of the fifteenth national/tenth conference on Artificial intelligence/Innovative applications of artificial intelligence
Multi-Objective Optimization Using Evolutionary Algorithms
Multi-Objective Optimization Using Evolutionary Algorithms
Evolutionary Algorithms for Solving Multi-Objective Problems
Evolutionary Algorithms for Solving Multi-Objective Problems
Multiobjective Optimization Using Evolutionary Algorithms - A Comparative Case Study
PPSN V Proceedings of the 5th International Conference on Parallel Problem Solving from Nature
Pareto-Front Exploration with Uncertain Objectives
EMO '01 Proceedings of the First International Conference on Evolutionary Multi-Criterion Optimization
The Supported Solutions Used as a Genetic Information in a Population Heuristics
EMO '01 Proceedings of the First International Conference on Evolutionary Multi-Criterion Optimization
Multiobjective evolutionary algorithms: classifications, analyses, and new innovations
Multiobjective evolutionary algorithms: classifications, analyses, and new innovations
Time-Energy Design Space Exploration for Multi-Layer Memory Architectures
Proceedings of the conference on Design, automation and test in Europe - Volume 1
Accelerating design space exploration using pareto-front arithmetics
ASP-DAC '03 Proceedings of the 2003 Asia and South Pacific Design Automation Conference
Multi-objective genetic algorithms: Problem difficulties and construction of test problems
Evolutionary Computation
Use of a genetic heritage for solving the assignment problem with two objectives
EMO'03 Proceedings of the 2nd international conference on Evolutionary multi-criterion optimization
Multi-level multi-objective genetic algorithm using entropy to preserve diversity
EMO'03 Proceedings of the 2nd international conference on Evolutionary multi-criterion optimization
PISA: a platform and programming language independent interface for search algorithms
EMO'03 Proceedings of the 2nd international conference on Evolutionary multi-criterion optimization
Performance assessment of multiobjective optimizers: an analysis and review
IEEE Transactions on Evolutionary Computation
Fuzzy classifier identification using decision tree and multiobjective evolutionary algorithms
International Journal of Approximate Reasoning
Developing a bioaerosol detector using hybrid genetic fuzzy systems
Engineering Applications of Artificial Intelligence
A population-based local search for solving a bi-objective vehicle routing problem
EvoCOP'07 Proceedings of the 7th European conference on Evolutionary computation in combinatorial optimization
Local search guided by path relinking and heuristic bounds
EMO'07 Proceedings of the 4th international conference on Evolutionary multi-criterion optimization
Structural and Multidisciplinary Optimization
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Nearly all Multi-Objective Evolutionary Algorithms (MOEA) rely on random generation of initial population. In large and complex search spaces, this random method often leads to an initial population composed of infeasible solutions only. Hence, the task of a MOEA is not only to converge towards the Pareto-optimal front but also to guide the search towards the feasible region. This paper proposes the incorporation of a novel method for constructing initial populations into existing MOEAs based on so-called Pareto-Front-Arithmetics (PFA). We will provide experimental results from the field of embedded system synthesis that show the effectiveness of our proposed methodology.