Search results for " Optimization"
showing 10 items of 2367 documents
Applying particle swarm optimization to the motion-cueing-algorithm tuning problem
2017
The MCA tuning problem consists in finding the best values for the parameters/coefficients of Motion Cueing Algorithms (MCA). MCA are used to control the movements of robotic motion platforms employed to generate inertial cues in vehicle simulators. This problem is traditionally approached with a manual pilot-in-the-loop subjective tuning, based on the opinion of several pilots/drivers. Instead, this paper proposes applying Particle Swarm Optimization (PSO) to solve this problem, using simulated motion platforms and objective indicators rather than subjective opinions. Results show that PSO-based tuning can provide a suitable solution for this complex optimization problem.
Using Genetic Algorithms for Optimizing the PPC in the Highway Horizontal Alignment Design.
2016
Various studies have emphasized the interesting advantages related to the use of new transition curves for improving the geometric design of highway horizontal alignments. In a previous paper, one of the writers proposed a polynomial curve, called a polynomial parametric curve (PPC), proving its efficiency in solving several design problems characterized by a very complex geometry (egg-shaped transition, transition between reversing circular curves, semidirect and inner-loop connections, and so on). The PPC also showed considerable advantages from a dynamic perspective, as evidenced by the analysis of the main dynamic variables related to motion (as well as rate of change of radial accelera…
Branch-and-Price-and-Cut for the Periodic Vehicle Routing Problem with Flexible Schedule Structures
2019
This paper addresses the periodic vehicle routing problem with time windows (PVRPTW). Therein, customers require one or several visits during a planning horizon of several periods. The possible visiting patterns (schedules) per customer are limited. In the classical PVRPTW, it is common to assume that each customer requires a specific visit frequency and offers all corresponding schedules with regular intervals between the visits. In this paper, we permit all kinds of schedule structures and the choice of the service frequency. We present an exact branch-and-price-and-cut algorithm for the classical PVRPTW and its variant with flexible schedules. The pricing problems are elementary shortes…
The directed profitable rural postman problem with incompatibility constraints
2017
[EN] In this paper, we study a variant of the directed rural postman problem (RPP) where profits are asso- ciated with arcs to be served, and incompatibility constraints may exist between nodes and profitable arcs leaving them. If convenient, some of the incompatibilities can be removed provided that penalties are paid. The problem looks for a tour starting and ending at the depot that maximizes the difference between collected profits and total cost as sum of traveling costs and paid penalties, while satisfying remaining incompatibilities. The problem finds application in the domain of road transportation service, and in particular in the context of horizontal collaboration among carriers …
The periodic rural postman problem with irregular services on mixed graphs
2019
Abstract In this paper, we deal with an extension of the rural postman problem in which some links of a mixed graph must be traversed a given number of times over a time horizon. These links represent entities that must be serviced a specified number of times in some subsets of days (or periods) of the time horizon. The aim is to design a set of minimum-cost tours, one for each day/period of the time horizon, that satisfy the service requirements. We refer to this problem as the periodic rural postman problem with irregular services (PRPP–IS). Some practical applications of the problem can be found in road maintenance operations and road network surveillance, for example. In order to solve …
Efficient Linear-Scaling Density Functional Theory for Molecular Systems
2013
Despite recent progress in linear scaling (LS) density function theory (DFT), the computational cost of the existing LS methods remains too high for a widespread adoption at present. In this work, we exploit nonorthogonal localized molecular orbitals to develop a series of LS methods for molecular systems with a low computational overhead. High efficiency of the proposed methods is achieved with a new robust two-stage variational procedure or by replacing the optimization altogether with an accurate nonself-consistent approach. We demonstrate that, even for challenging condensed-phase systems, the implemented LS methods are capable of extending the range of accurate DFT simulations to molec…
Modélisation du comportement des agriculteurs face au risque dans un modèle de programmation mathématique positive (PMP) à grande échelle
2017
Agricultural production is characterized for being a risky business due to weather variability, market instability, plant diseases as well as climate change and political economy uncertainty. The modelling of risk at farm level is not new, however, the inclusion of risk in Positive Mathematical Programming (PMP) models is particularly challenging. Most of the few existing PMP-risk approaches have been conducted at farm-type level and for a very limited and specific sample of farms. This implies that the modelling of risk and uncertainty at individual farm level and in a large scale system is still a challenging task. The aim of this paper is to formulate, estimate and test a robust methodol…
SAMSLAM: Simulated Annealing Monocular SLAM
2013
This paper proposes a novel monocular SLAM approach. For a triplet of successive keyframes, the approach inteleaves the registration of the three 3D maps associated to each image pair in the triplet and the refinement of the corresponding poses, by progressively limiting the allowable reprojection error according to a simulated annealing scheme. This approach computes only local overlapping maps of almost constant size, thus avoiding problems of 3D map growth. It does not require global optimization, loop closure and back-correction of the poses.
Non-convex power allocation games in MIMO cognitive radio networks
2013
Consideramos un escenario de reparto del espectro, basado en la detección, en una red de radio cognitiva MIMO donde el objetivo general es maximizar el rendimiento total de cada usuario de radio cognitiva optimizando conjuntamente la operación de detección y la asignación de potencia en todos los canales, bajo una restricción de interferencia para los usuarios primarios. Los problemas de optimización resultantes conducen a un juego no convexo, que presenta un nuevo desafío a la hora de analizar los equilibrios de este juego. Con el fin de hacer frente a la no convexidad del juego, utilizamos un nuevo concepto relajado de equilibrio, el equilibrio cuasi-Nash (QNE). Se demuestran las condicio…
On the Almost Everywhere Convergence of Multiple Fourier-Haar Series
2019
The paper deals with the question of convergence of multiple Fourier-Haar series with partial sums taken over homothetic copies of a given convex bounded set $$W\subset\mathbb{R}_+^n$$ containing the intersection of some neighborhood of the origin with $$\mathbb{R}_+^n$$ . It is proved that for this type sets W with symmetric structure it is guaranteed almost everywhere convergence of Fourier-Haar series of any function from the class L(ln+L)n−1.