Study of a Bi-Vertical Axis Turbines Farm Using the Actuator Cylinder Method

Vertical axis turbines, which extract kinetic energy from currents, can produce electricity independently from a current’s direction. Hence, this type of turbines raises interest for harvesting energy from tidal currents, where flow changes direction during flood and ebb tides, and where currents present large variation of direction during tide. Methods for representing vertical axis turbines in tidal farms should be implemented in order to predict correctly power production with an acceptable time cost. The Actuator Cylinder (AC) is one of them. Numerical results in terms of wakes, with the study of velocity profiles, and efforts are compared to experiences, as well as showed that the method is sufficiently accurate and for a reasonable computing time, which is of prime importance for tidal turbines farms studies. The Actuator Cylinder method is implemented in ANSYS Fluent in a 2D stationary resolution. The method is then applied to a double levels of two counter-rotating rotors marine turbine designed by Hydroquest. Wake and power production of a single turbine and several farm configurations are studied under different current conditions (magnitude and direction).

Combining Heuristics with Simulation and Fuzzy Logic to Solve a Flexible-Size Location Routing Problem under Uncertainty

The location routing problem integrates both a facility location and a vehicle routing problem. Each of these problems are NP-hard in nature, which justifies the use of heuristic-based algorithms when dealing with large-scale instances that need to be solved in reasonable computing times. This paper discusses a realistic variant of the problem that considers facilities of different sizes and two types of uncertainty conditions. In particular, we assume that some customers’ demands are stochastic, while others follow a fuzzy pattern. An iterated local search metaheuristic is integrated with simulation and fuzzy logic to solve the aforementioned problem, and a series of computational experiments are run to illustrate the potential of the proposed algorithm.

A New Genetic Algorithm Encoding for Coalition Structure Generation Problems

Genetic algorithms have proved to be a useful improvement heuristic for tackling several combinatorial problems, including the coalition structure generation problem. In this case, the focus lies on selecting the best partition from a discrete set. A relevant issue when designing a Genetic algorithm for coalition structure generation problems is to choose a proper genetic encoding that enables an efficient computational implementation. In this paper, we present a novel hybrid encoding, and we compare its performance against several genetic encoding proposed in the literature. We show that even in difficult instances of the coalition structure generation problem, the proposed approach is a competitive alternative to obtaining good quality solutions in reasonable computing times. Furthermore, we also show that the encoding relevance increases as the number of players increases.

Monte Carlo simulation for a gas of hard spheres in d-dimensional space: Equilibrium structure and state equations

In this work, we emphasize that it is possible using a personal computer to perform a MonteCarlo simulations in a reasonable computing time, and find the equilibrium structure of a hardsphere gas for a Euclidean multi-dimensional spaces. We study the properties of equilibrium and determine the equation of state of gas of hard spheres in Euclidean spaces from two to seven dimensions. The results show that the pressure is in agreement with different theoretical models based on virial expansion in spaces from two to five dimensions, also our results are extended for seven dimensions. As expected, it was found that the system of hard spheres loses its structure and the pressure of the system decreases when the dimension of the space increases.

Designing Parallel Meta-Heuristic Methods

Meta-heuristics represent powerful tools for addressing hard combinatorial optimization problems. However, real life instances usually cannot be treated efficiently in “reasonable” computing times. Moreover, a major issue in meta-heuristic design and calibration is to provide high performance solutions for a variety of problems. Parallel meta-heuristics aim to address both issues. The objective of this chapter is to present a state-of-the-art survey of the main parallelization ideas and strategies, and to discuss general design principles applicable to all meta-heuristic classes. To achieve this goal, the authors explain various paradigms related to parallel meta-heuristic development, where communications, synchronization, and control aspects are the most relevant. They also discuss implementation issues pointing out the characteristics of shared and distributed memory multiprocessors as target architectures. All these topics are illustrated by the examples from recent literature related to the parallelization of various meta-heuristic methods. Here, the authors focus on Variable Neighborhood Search and Bee Colony Optimization.

An Effective Genetic Algorithm for the Vehicle Routing Problem with Multiple Depots

The vehicle routing problem with multiple depots was considered in this paper, and a genetic algorithm for the proposed problem was designed to minimize the vehicle number and total travel distance. Performances are compared with other heuristics recently published in the literature, the computational results show that the proposed approaches produce high quality results within a reasonable computing time.

An Effective Tabu Search for Vehicle Routing Problem with Pickup and Delivery Service

The vehicle routing problem with delivery and pick-up service was considered in this paper. A tabu search was proposed to determine the optimal set of routes to totally satisfy both the delivery and pick-up demand. Performances are compared with other heuristics appeared in the literature recently by the bench-mark data sets. The computational results show that the proposed approaches produce high quality results within a reasonable computing time.

THE LANDAU DISTRIBUTION FOR CHARGED PARTICLES TRAVERSING THIN FILMS

The Landau distribution as well as its first and second momenta are well suited for describing the energy loss of charged particles traversing a thin layer of matter. At present, just rational approximations and asymptotic expressions for these functions were obtained. In this paper we present a direct calculation of the integral representation of these functions obtaining perturbative and nonperturvative solutions expressed in terms of fast convergent series. We also provide a simple numerical algorithm which allows to control speed and precision of the results. The testing runs have provided, in reasonable computing times, correct results up to 13-14 significant digits on the density and distribution functions and 9-10 on the first and second momenta. If necessary, this accuracy could be improved by adding more coefficients to the algorithm.

An algorithm for computing the reversal degree of planar topological graphs

International audience One characteristic of planar topological graphs is the reversal degree. In this paper, we propose an improve algorithm for calculating the reversal degree of a planar topological graphs. This algorithm explores various possible cases following the descending method. Practical tests carried out on machine, using graphs with more than fifty internal vertices of odd degree, have been realized within reasonable computing time. Le degré de retournement est une caractéristique des graphes planaires topologiques. Dans cet article nous proposons un algorithme amélioré pour calculer le degré de retournement d'un graphe planaire topologique. Cet algorithme explore les différents cas possibles suivant une méthode descendante. Son implémentation sur machine a donné lieu à des tests sur des cas pratiques, ceci en des temps de calcul tout à fait raisonnables, sur des graphes dont l'un comporte plus d'une cinquantaine de sommets intérieurs de degré impair