Searched for: subject%3A%22Algorithms%22
(1 - 7 of 7)
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van Maris, Bart (author)
Algorithmic planners occasionally waste effort and thus computing time trying to solve certain tasks, as they often lack the human ability to recognize essential paths. These essential paths, termed landmarks, are vital for optimizing planning processes. This study revisits landmark-based planning methods introduced by Richter, Helmert, and...
bachelor thesis 2024
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Bien, Benedict (author)
Decision trees are integral to machine learning, with their robustness being a critical measure of effectiveness against adversarial data manipulations. Despite advancements in algorithms, current solutions are either optimal but lack scalability or scale well, but do not guarrantee optimality. This paper presents a novel adaptation of the...
bachelor thesis 2023
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Groenheide, Jeroen (author)
Multi-Level variants of classic optimisation problems are becoming more noteworthy as the complexity of real life applications increases. In this research we investigate the Multi-Level Bin Packing optimisation problem, which models, for example, global logistics and part manufacturing. We will look at the performance of solving Integer Linear...
bachelor thesis 2022
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Numan, Tim (author)
This papers examines an ant colony optimization approach for solving a specific variant of the Flexible Job Shop Problem faced by the Dutch chemistry company DSM. Jobs consisting of operations on a specific enzyme need to be scheduled as efficiently as possible on groups of available machines. The most interesting requirement upon the general...
bachelor thesis 2022
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van der Kamp, Kevin (author)
Efficient reasoning about time is crucial for robot operation, planning, and many other applications. A widespread representation used for reasoning about time is the so-called Simple Temporal Network (STN). Students at TU Delft previously developed and implemented algorithms for performing incremental reasoning over STNs. These algorithms...
bachelor thesis 2018
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van Bekkum, Rob (author)
Decision-theoretic planning techniques are increasingly being used to obtain (optimal) plans for domains involving uncertainty, which may be present in the form of the controlling agent's actions, its percepts, or exogenous factors in the domain. These techniques build on detailed probabilistic models of the underlying system, for which Markov...
master thesis 2017
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van der Linden, Koos (author)
A recent development in the field of discrete optimization is the combined use of (binary) decision diagrams (DD) and branch and bound for optimization. This method has been shown to outperform integer linear programming on several classic problems. The performance of DDs in integer optimization raises the question if this method can be extended...
master thesis 2017
Searched for: subject%3A%22Algorithms%22
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