Genetic programming: on the programming of computers by means of natural selection
Genetic programming: on the programming of computers by means of natural selection
Genetic learning of dynamic scheduling within a simulation environment
Computers and Operations Research - Special issue: heuristic, genetic and tabu search
Neural fuzzy systems: a neuro-fuzzy synergism to intelligent systems
Neural fuzzy systems: a neuro-fuzzy synergism to intelligent systems
Genetic Algorithms and Grouping Problems
Genetic Algorithms and Grouping Problems
Foundations of Neural Networks, Fuzzy Systems, and Knowledge Engineering
Foundations of Neural Networks, Fuzzy Systems, and Knowledge Engineering
Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
Evolutionary optimization within an intelligent hybrid system for design integration
Artificial Intelligence for Engineering Design, Analysis and Manufacturing
Artificial Intelligence for Engineering Design, Analysis and Manufacturing
Artificial Intelligence Review
EvoCOP'08 Proceedings of the 8th European conference on Evolutionary computation in combinatorial optimization
Improving the genetic algorithms performance in simple assembly line balancing
ICCSA'06 Proceedings of the 2006 international conference on Computational Science and Its Applications - Volume Part V
Interval type-2 fuzzy modelling and simulated annealing for real-world inventory management
HAIS'11 Proceedings of the 6th international conference on Hybrid artificial intelligent systems - Volume Part I
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The use of hybrid artificial intelligence systems in operations management has grown during the last years given their ability to tackle combinatorial and NP hard problems. Furthermore, operations management problems usually involve imprecision, uncertainty, vagueness, and high-dimensionality. This paper examines recent developments in the field of hybrid artificial intelligence systems for those operations management problems where hybrid approaches are more representative: design engineering, process planning, assembly line balancing, and dynamic scheduling.