A review of machine learning applications in fuzzing
GJ Saavedra, KN Rodhouse, DM Dunlavy… - arXiv preprint arXiv …, 2019 - arxiv.org
Fuzzing has played an important role in improving software development and testing over
the course of several decades. Recent research in fuzzing has focused on applications of …
the course of several decades. Recent research in fuzzing has focused on applications of …
Meta-analysis of metaheuristics: Quantifying the effect of adaptiveness in adaptive large neighborhood search
Research on metaheuristics has focused on (novel) algorithmic development and on
competitive testing, both of which have been frequently argued to yield little generalizable …
competitive testing, both of which have been frequently argued to yield little generalizable …
Boosting combinatorial problem modeling with machine learning
M Lombardi, M Milano - arXiv preprint arXiv:1807.05517, 2018 - arxiv.org
In the past few years, the area of Machine Learning (ML) has witnessed tremendous
advancements, becoming a pervasive technology in a wide range of applications. One area …
advancements, becoming a pervasive technology in a wide range of applications. One area …
Solving segment routing problems with hybrid constraint programming techniques
Segment routing is an emerging network technology that exploits the existence of several
paths between a source and a destination to spread the traffic in a simple and elegant way …
paths between a source and a destination to spread the traffic in a simple and elegant way …
Multi-objective large neighborhood search
Abstract Large neighborhood search (LNS)[25] is a framework that combines the
expressiveness of constraint programming with the efficiency of local search to solve …
expressiveness of constraint programming with the efficiency of local search to solve …
Explanation-based large neighborhood search
One of the most well-known and widely used local search techniques for solving
optimization problems in Constraint Programming is the Large Neighborhood Search (LNS) …
optimization problems in Constraint Programming is the Large Neighborhood Search (LNS) …
Cost impact guided LNS
M Lombardi, P Schaus - Integration of AI and OR Techniques in Constraint …, 2014 - Springer
Abstract In Large Neighborhood Search (LNS)[14], a problem is solved by repeatedly
exploring (via tree search) a neighborhood of an incumbent solution. Whenever an …
exploring (via tree search) a neighborhood of an incumbent solution. Whenever an …
An exploration-exploitation compromise-based adaptive operator selection for local search
N Veerapen, J Maturana, F Saubion - … of the 14th annual conference on …, 2012 - dl.acm.org
This paper deals with the adaptive selection of operators in the context of local search (LS).
In evolutionary algorithms, diversity is a key concept. We consider a related idea: the …
In evolutionary algorithms, diversity is a key concept. We consider a related idea: the …
Variable objective large neighborhood search: A practical approach to solve over-constrained problems
P Schaus - 2013 IEEE 25th International Conference on Tools …, 2013 - ieeexplore.ieee.org
Everyone having used Constraint Programming (CP) to solve hard combinatorial
optimization problems with a standard exhaustive Branch & Bound Depth First Search (B&B …
optimization problems with a standard exhaustive Branch & Bound Depth First Search (B&B …
[PDF][PDF] Advanced modelling and search techniques for routing and scheduling problems.
C Thomas - 2023 - dial.uclouvain.be
This thesis presents the application of several Constraint Programming (CP) techniques to
combinatorial problems. In particular, hybrid scheduling and routing problems such as Dial …
combinatorial problems. In particular, hybrid scheduling and routing problems such as Dial …