Optimization of control parameters for genetic algorithms
IEEE Transactions on Systems, Man and Cybernetics
Future paths for integer programming and links to artificial intelligence
Computers and Operations Research - Special issue: Applications of integer programming
Meta-Heuristics: Advances and Trends in Local Search Paradigms for Optimization
Meta-Heuristics: Advances and Trends in Local Search Paradigms for Optimization
Soft Computing and Fuzzy Logic
IEEE Software
Fuzzy Sets Based Heuristics for Optimization
Fuzzy Sets Based Heuristics for Optimization
Using memory and fuzzy rules in a co-operative multi-thread strategy for optimization
Information Sciences: an International Journal
Evolutionary algorithms + domain knowledge = real-world evolutionary computation
IEEE Transactions on Evolutionary Computation
On the conflict between inducing confusion and attaining payoff in adversarial decision making
Information Sciences: an International Journal
Using machine learning in a cooperative hybrid parallel strategy of metaheuristics
Information Sciences: an International Journal
Towards a new strategy for solving fuzzy optimization problems
Fuzzy Optimization and Decision Making
QoS-based cooperative algorithm for integral multi-commodity flow problem
Computer Communications
A multi-objective genetic algorithm for cardinality constrained fuzzy portfolio selection
Fuzzy Sets and Systems
Rough sets in the Soft Computing environment
Information Sciences: an International Journal
Review: Soft computing applications in customer segmentation: State-of-art review and critique
Expert Systems with Applications: An International Journal
| Hi-index | 0.21 |
Although as such one dates back the idea of setting the area of soft computing to 1990, it was in 1994 that L.A. Zadeh established his worldwide accepted definition of soft computing. As it is well known since the seminal definition of a fuzzy set, different equivalent definitions of the concept have been proposed, analyzed and used. But, in spite of the former main constituents could be currently others and hence they should be revised, and the same cannot be said of soft computing. From this point of view, in order to narrow this gap, in this paper the role played until now by these main soft computing ingredients is analyzed, and then an original proposal of the new constituents, mainly focused on the introduction of the broader topic of metaheuristics instead of evolutionary algorithms, is justified, presented and described.