Stability of the Malvinas Current

Deterministic and probabilistic tools from nonlinear dynamics are used to assess enduring near-surface Lagrangian aspects of the Malvinas Current. The deterministic tools are applied on a multi-year record of velocities derived from satellite altimetry data, revealing a resilient cross-stream transport barrier. This is composed of shearless-parabolic Lagrangian coherent structures (LCS), which, extracted over sliding time windows along the multi-year altimetry-derived velocity record, lie in near coincidental position. The probabilistic tools are applied on a large collection of historical satellite-tracked drifter trajectories, revealing weakly communicating flow regions on either side of the altimetry-derived barrier. Shearless-parabolic LCS are detected for the first time from altimetry data, and their significance is supported on satellite-derived ocean color data, which reveal shapes that quite closely resemble the peculiar V shapes, dubbed `chevrons,' that have recently confirmed the presence of similar LCS in the atmosphere of Jupiter. Finally, using in-situ velocity and hydrographic data, conditions for symmetric stability are found to be satisfied, suggesting a duality between Lagrangian and Eulerian stability for the Malvinas Current.Comment: Submitted to Scientific Report

A process for automated class scheduling at Ashesi

Applied project submitted to the Department of Computer Science, Ashesi University College, in partial fulfillment of Bachelor of Science degree in Computer Science, April 2014At the beginning of every semester, the registrar at Ashesi University goes through the laborious task of either manually or semi-automatically developing a course schedule. Very often, after the schedule has been developed, conflicts are realized in the various schedules. Conflicts are categorized into student, lecturer and room conflicts. An open source software, FET was recently used by the university to help develop schedules for the courses. This project is an attempt to review the ways in which the automation process can be enhanced in order to potentially reduce the conflicts faced. At the heart of automated course scheduling is the algorithm being used. Any effort made at enhancing the scheduling process in Ashesi will require an efficient algorithm. This paper begins with a background on scheduling, an extensive research on existing approaches and algorithms follows. The algorithms reviewed include the Multi-Agent System approach, Sequential methods, Constraint Based Methods, Genetic Algorithms, Simulated Annealing, Particle Swarm optimization and Tabu Search. The algorithm used in the FET software is also reviewed. These techniques are compared based on their computational time, ease of implementation, solution quality and constraint handling. Based on the literature, it is realized that Particle Swarm Optimization is potentially the best algorithm with respect to the set criteria. A basic version of the Particle Swarm Algorithm is implemented and tested and the results compared with the results from testing the current FET software algorithm, recursive swapping. The outcome implies that recursive swapping, can produce good solutions but Particle Swarm Optimization is easier to implement.Ashesi University CollegeGrade: less than

Dueling CSP representations: Local search in the primal versus dual constraint graph.

Constraint Satisfaction Problems (CSPs) can be used to represent and solve many problems in Artificial Intelligence and the real world. When solving Constraint Satisfaction Problems, many of the methods developed and studied have focused only on the solution of binary CSPs while a large portion of real life problems are naturally modeled as non-binary CSPs. In this thesis we have designed an empirical study to investigate the behaviour of several local search methods in primal and dual constraint graph representations when solving non-binary CSPs. Local search methods tend to find a solution quickly since they generally give up the guarantee of completeness for polynomial time performance. Such local search methods include simple hill-climbing, steepest ascent hill-climbing and min-conflicts heuristics hill-climbing. We evaluate the performance of these three algorithms in each representation for a variety of parameter settings and we compare the search time cost means of two groups to support the comparison. Our comparison shows that we can use local search to solve a CSP with tight constraints in its dual representation and gain a better performance than using it in its primal representation. When constraints are getting looser, using local search in primal representation is a better choice. Among the three local search methods used in our empirical study, min-conflicts heuristics hill-climbing always gain the best performance while steepest ascent hill-climbing tends to have the worst performance and simple hill climbing is in the middle or sometimes it is the best. Paper copy at Leddy Library: Theses & Major Papers - Basement, West Bldg. / Call Number: Thesis2004 .H824. Source: Masters Abstracts International, Volume: 43-01, page: 0237. Adviser: Scott Goodwin. Thesis (M.Sc.)--University of Windsor (Canada), 2004

A wide-ranging computational comparison of high-performance graph colouring algorithms

This paper reviews the current state of the literature surrounding methods for the general graph colouring problem and presents a broad comparison of six high-performance algorithms, each belonging to one of the main algorithmic schemes identified. Unlike many previous computational studies in graph colouring, a large range of both artificially generated and real-world graphs are considered, culminating in over 40,000 individual trials that have consumed more than a decade of computation time in total. The picture painted by the comparison is complex, with each method outperforming all others on at least one occasion; however, general patterns are also observed, particularly with regards to the advantages of hybridising local-search techniques with global-based operators

Nouveaux algorithmes, bornes et formulations pour les problèmes de la clique maximum et de la coloration minimum

Thèse numérisée par la Direction des bibliothèques de l'Université de Montréal

Optimization by quantum annealing for the graph colouring problem

Quantum annealing is the quantum equivalent of the well known classical simulated annealing algorithm for combinatorial optimization problems. Despite the appeal of the approach, quantum annealing algorithms competitive with the state of the art for specific problems hardly exist in the literature. Graph colouring is a difficult problem of practical significance that can be formulated as combinatorial optimization. By introducing a symmetry-breaking problem representation, and finding fast incremental techniques to calculate energy changes, a competitive graph colouring algorithm based on quantum annealing is derived. This algorithm is further enhanced by tuning simplification techniques; replica spacing techniques to increase robustness; and a messaging protocol, which enables quantum annealing to efficiently take advantage of multiprocessor environments. Additionally, observations of some patterns in the tuning for random graphs led to a more effective algorithm able to find new upper bounds for several widely-used benchmark graphs, some of which had resisted improvement in the last two decades