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GECCO
2007
Springer
182views Optimization» more  GECCO 2007»
16 years 28 days ago
An analysis of the effects of population structure on scalable multiobjective optimization problems
Multiobjective evolutionary algorithms (MOEA) are an effective tool for solving search and optimization problems containing several incommensurable and possibly conflicting objec...
Michael Kirley, Robert L. Stewart
GECCO
2007
Springer
190views Optimization» more  GECCO 2007»
16 years 28 days ago
Interactive evolutionary multi-objective optimization and decision-making using reference direction method
In this paper, we borrow the concept of reference direction approach from the multi-criterion decision-making literature and combine it with an EMO procedure to develop an algorit...
Kalyanmoy Deb, Abhishek Kumar
GECCO
2007
Springer
558views Optimization» more  GECCO 2007»
16 years 28 days ago
A chain-model genetic algorithm for Bayesian network structure learning
Bayesian Networks are today used in various fields and domains due to their inherent ability to deal with uncertainty. Learning Bayesian Networks, however is an NP-Hard task [7]....
Ratiba Kabli, Frank Herrmann, John McCall
GECCO
2007
Springer
154views Optimization» more  GECCO 2007»
16 years 28 days ago
A novel ab-initio genetic-based approach for protein folding prediction
In this paper, a model based on genetic algorithms for protein folding prediction is proposed. The most important features of the proposed approach are: i) Heuristic secondary str...
Sergio Raul Duarte Torres, David Camilo Becerra Ro...
GECCO
2007
Springer
174views Optimization» more  GECCO 2007»
16 years 28 days ago
Investigating data-flow coverage of classes using evolutionary algorithms
It is not unusual for a software development organization to expend 40 percent of total project effort on testing, which can be a very laborious and time-consuming process. Thus, ...
Konstantinos Liaskos, Marc Roper, Murray Wood