Searched for: contributor%3A%22Demirovi%C4%87%2C+E.+%28mentor%29%22
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Tatabitovska, Ana (author)
Maximum Satisfiability (MaxSAT) is a known problem within the optimization field which has led many different solving approaches to be devised in the last several decades. From Linear Search to unsatisfiable core-based solvers, many MaxSAT algorithms rely on cardinality constraints to express how many soft clauses can be violated at most....
master thesis 2023
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Zoumis, Angelos (author)
<br/>Constraint programming solvers provide a generalizable approach to finding solutions for optimization problems. However, when comparing the performance of constraint programming solvers to the performance of a heuristic solver for an optimization problem such as cluster editing, the heuristic solver is able to find near-optimal and optimal...
master thesis 2023
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Marijnissen, Imko (author)
Core-guided solvers and Implicit Hitting Set (IHS) solvers have become ubiquitous within the field of Maximum Satisfiability (MaxSAT). While both types of solvers iteratively increase the solution cost until a satisfiable solution is found, the manner in which this relaxation is performed leads to the belief that these techniques are wholly...
master thesis 2023
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Tudor, Iarina (author)
This paper provides a novel method of solving the resource-constrained project scheduling problem (RCPSP) with logical constraints (RCPSP-log) using satisfiability (SAT) solving and integrating variable selection heuristics. The extension provides two additional precedences: OR constraints and bidirectional (BI) relations, making it possible to...
bachelor thesis 2023
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Lenssen, Tijs (author)
The Variable State Independent Decaying Sum (VSIDS) heuristic is one of the most effective variable selection heuristics for Conflict-Driven Clause-Learning (CDCL) SAT solvers. It works by keeping track of the activity values for each variable, which get bumped and decayed based on conflict analysis. These activity values usually start out...
bachelor thesis 2023
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Hellouin de Ménibus, George (author)
This paper presents a new greedy heuristic to extend SAT Solvers when solving the Preemptive resource-constrained project scheduling problem (PRCPSP-ST). The heuristic uses domain-specific knowledge to generate a fixed order of variable selection. We also extend previous work into encoding PRCPSP-ST by providing an alternative upper bound. The...
bachelor thesis 2023
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Pugatšov, Artjom (author)
This paper solves job sequencing with one common and multiple secondary resources (JSOCMSR) problem by encoding it as a Boolean satisfiability (SAT) problem and applying domain-specific heuristics to improve the SAT solver’s performance. JSOCMSR problem is an NP-hard scheduling problem where each job utilizes two resources: a shared resource and...
bachelor thesis 2023
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Tsvetkov, Denis (author)
The multi-mode resource-constrained project scheduling problem (MRCPSP) is an extension of the resource-constrained project scheduling problem (RCPSP), which allows activities to be executed in multiple modes. The state-of-the-art solutions for solving this NP-Hard problem are dedicated algorithms and (meta-)heuristics. However, this paper...
bachelor thesis 2023
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Segalini, Giulio (author)
The Algorithm Selection Problem is a relevant question in computer science that would enable us to predict which algorithm would perform better on a given instance of a problem. <br/>Different solutions have been proposed, either using Mixed Integer Programming or machine learning models, but both suffer from either poor scalability, no...
bachelor thesis 2023
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KINDYNIS, Chrysanthos (author)
In this paper, we tackle the problem of creating decision trees that are both optimal and individually fair. While decision trees are popular due to their interpretability, achieving optimality can be difficult. Existing approaches either lack scalability or fail to consider individual fairness. To address this, we define individual fairness as...
bachelor thesis 2023
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van den Bos, Mim (author)
Decision trees make decisions in a way interpretable to humans, this is important when machines are increasingly used to aid in making high-stakes and socially sensitive decisions. While heuristics have been used for a long time to find decision trees with reasonable accuracy, recent approaches find fully optimal trees. Due to the computational...
bachelor thesis 2023
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Huisman, Tim (author)
Survival analysis revolves around studying and predicting the time it takes for a particular event to occur. In clinical trials on terminal illnesses, this is usually the time from the diagnosis of a patient until their death. Estimating the odds of survival of a new patient can be done by analyzing survival data from past patients in similar...
bachelor thesis 2023
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Götz, Valentijn (author)
Decision tree learning is widely done heuristically, but advances in the field of optimal decision trees have made them a more prominent subject of research. However, current methods for optimal decision trees tend to overlook the metric of robustness. Our research wants to find out whether the robustness of optimal decision trees can be...
bachelor thesis 2023
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Zeng, Henwei (author)
Several algorithms can often be used to solve a complex problem, such as the SAT problem or the graph coloring problem. Those algorithms differ in terms of speed based on the size or other features of the problem. Some algorithms perform much faster on a small size while others perform noticeably better on a larger instance. The optimization...
bachelor thesis 2023
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Butzelaar, Sven (author)
Machine learning can be used to classify patients in a hospital. Here, the classifier has to minimize the cost of misclassifying the patient and minimize the costs of the tests. Unfortunately, obtaining features may be costly, e.g., taking blood tests or doing an x-ray scan. Furthermore, it is possible that acquiring those test results may take...
bachelor thesis 2023
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van Dijk, Jeroen (author)
The Multi-Agent Path Finding (MAPF) problem is the problem of planning paths for multiple agents without any collisions. There are also many variants such as the waypoint variant, where each agent also has a set of waypoints it must visit before reaching its goal. The colored variant, in which the agents are grouped into teams and each team has...
master thesis 2022
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Nardi Dei Da Filicaia Dotti, Andrea (author)
In this paper we give a historical and theoretical background to minimal triangulation and its relation to minimal separators.<br/>We introduce a new type of minimal separators, the minimal meta separator, which its size is a lower bound for the treewidth problem, its fill-in is a lower bound for the minimum fill-in problem and can be used for...
master thesis 2022
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Miguel Teixeira de Mendonça, João (author)
The multi-mode resource-constrained project scheduling problem (MRCPSP) is an NP-hard scheduling problem that concerns activities with several execution modes connected by precedence relations. Precedence relations define a partial ordering in which activities must be processed. The execution mode of an activity defines its processing time and...
bachelor thesis 2022
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Dashtevski, Filip (author)
We study the prize-collecting job scheduling problem with one common and multiple secondary resources, where the target is to collect the biggest score possible by constructing a feasible schedule with given constraints of jobs and resources. Many scheduling configurations, where a single asset can be used by all jobs separately and a set of...
bachelor thesis 2022
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Pleunes, Jelle (author)
In this paper, a variant of the resource-constrained project scheduling problem is discussed. This variant introduces time-dependence for resource capacities and requests, making the problem a more realistic model for many practical applications such as production scheduling and medical research project planning. The main aim of this paper is to...
bachelor thesis 2022
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