We present the design of an algorithm to maximize the number of bugs found for black-box
mutational fuzzing given a program and a seed input. The major intuition is to leverage white …

The Mallows model is a popular distribution for ranked data. We empirically and theoretically
analyze how the properties of rankings sampled from the Mallows model change when …

In this work, we explore different multi-armed bandit-based hyper-heuristics applied to the
multi-objective permutation flow shop problem. It is a scheduling problem which has been …

Rank aggregation is widely used in group decision making and many other applications,
where it is of interest to consolidate heterogeneous ordered lists. Oftentimes, these rankings …

Global random search algorithms are characterized by using probability distributions to
optimize problems. Among them, generative methods iteratively update the distributions by …

Abstract The Quadratic Assignment Problem (QAP) is a well-known permutation-based
combinatorial optimization problem with real applications in industrial and logistics …

High-centrality nodes have disproportionate influence on the behavior of a network;
therefore controlling such nodes can efficiently steer the system to a desired state. Existing …

Esta tesis est¿ a dedicada al aprendizaje y muestreo de los modelos de probabilidadsobre
permutaciones basados en distancias. En concreto, las distancias consideradasson la¿ de …

Solving a problem by using metaheuristic algorithms requires the evaluation of a large
number of potential solutions. This paper presents a theoretical and experimental study of …

Recently, distance-based exponential probability models, such as Mallows and Generalized
Mallows, have demonstrated their validity in the context of estimation of distribution …