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Fagerholt (2004) has also developed a computer-based decision support system for fleet scheduling based on heuristic algorithms.
Consequently, practical DT algorithms are based on heuristic algorithms such as the greedy algorithm where locally optimal decisions are made at each node.
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In general, many of the solutions reported in literature for searching optimal UEP strategies are based on heuristic methods or use optimization algorithms [30 33].
Algorithms based on heuristic approaches reduce the effort in parameter identification and computation time.
Some of these algorithms are based on heuristic approaches, such as 2D sort and Sugiyama-based methods [5].
This paper presents the cLHS method with a search algorithm based on heuristic rules combined with an annealing schedule.
Then, the iterative ADP algorithm based on heuristic dynamic programming is introduced to deal with the regulation problem with convergence analysis.
All the above algorithms are based on heuristic methods, not mathematical formulations.
Many BN structure learning algorithms are based on heuristic search techniques with the likelihood approximation because of the infeasible computational complexity.
Now, we introduce the pseudocode of this the heuristic algorithm, and then we give an application based on this heuristic algorithm.
Under faster manipulator performance, an approximation algorithm based on heuristics and a local search was shown to produce near-optimal harvest assignments.
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