Heuristics derived from reading comprehension research are employed to obtain additional scoring features.
For larger instances, two heuristics derived from the MILP are designed.
The developed algorithm is based on the branch-and-bound approach and heuristics derived from engineering insights.
A comparative numerical analysis of the performance of the optimal assignment policy and of several heuristics, derived from practice, is performed.
Two different classes of decision rules could generate this behavior: rules that are optimal conditional on utility functions departing from risk neutrality, or heuristics derived from limited cognitive processing capacities and satisficing.
The view of perceptual heuristics [11], [13] posits that the biases or distortions occur due to heuristics derived from principles of perceptual organization.
We investigate structural properties of optimal solutions, show that the simplest variant is NP-hard, analyze the worst-case performance of natural greedy heuristics, derive a 4-approximation algorithm, and conduct a small computational study.
By combining a column and row generation technique and a strong formulation including forcing constraints, this heuristic derives high quality results, and computational effort can be reduced considerably.
Artificial Immune System (AIS) optimization is an emerging heuristic method derived from the human immune system.
