Search results for "A* algorithm"
showing 10 items of 2538 documents
Genetic Algorithm Optimized Grid-based RF Fingerprint Positioning in Heterogeneous Small Cell Networks
2015
In this paper we propose a novel optimization algorithm for grid-based RF fingerprinting to improve user equipment (UE) positioning accuracy. For this purpose we have used Multi-objective Genetic Algorithm (MOGA) which enables autonomous calibration of gridcell layout (GCL) for better UE positioning as compared to that of the conventional fingerprinting approach. Performance evaluations were carried out using two different training data-sets consisting of Minimization of Drive Testing measurements obtained from a dynamic system simulation in a heterogeneous LTE small cell environment. The robustness of the proposed method has been tested analyzing positioning results from two different area…
Optimization of photovoltaic energy production through an efficient switching matrix
2013
This work presents a preliminary study on the implementation of a new system for power output maximization of photovoltaic generators under non-homogeneous conditions. The study evaluates the performance of an efficient switching matrix and the relevant automatic reconfiguration control algorithms. The switching matrix is installed between the PV generator and the inverter, allowing a large number of possible module configurations. PV generator, switching matrix and the intelligent controller have been simulated in Simulink. The proposed reconfiguration system improved the energy extracted by the PV generator under non-uniform solar irradiation conditions. Short calculation times of the pro…
Nature That Breeds Solutions
2012
Nature has always been a source of inspiration. Over the last few decades, it has stimulated many successful techniques, algorithms and computational applications for dealing with large, complex and dynamic real world problems. In this article, the authors discuss why nature-inspired solutions have become increasingly important and favourable for tackling the conventionally-hard problems. They also present the concepts and background of some selected examples from the domain of natural computing, and describe their key applications in business, science and engineering. Finally, the future trends are highlighted to provide a vision for the potential growth of this field.
Split-Delivery Capacitated Arc-Routing Problem: Lower Bound and Metaheuristic
2010
International audience; This paper proposes lower and upper bounds for the split-delivery capacitated arc-routing problem (SDCARP), a variant of the capacitated arc-routing problem in which an edge can be serviced by several vehicles. Recent papers on related problems in node routing have shown that this policy can bring significant savings. It is also more realistic in applications such as urban refuse collection, where a vehicle can become full in the middle of a street segment. This work presents the first lower bound for the SDCARP, computed with a cutting plane algorithm and an evolutionary local search reinforced by a multistart procedure and a variable neighborhood descent. Tests on …
Optimal Electrical Distribution Systems Reinforcement Planning Using Gas Micro Turbines by Dynamic Ant Colony Search Algorithm
2007
Distribution systems management is becoming an increasingly complicated issue due to the introduction of new energy trading strategies and new technologies. In this paper, an optimal reinforcement strategy to provide reliable and economic service to customers in a given time frame is investigated. In the new deregulated energy market and considering the incentives coming from the political and economical fields, it is reasonable to consider distributed generation (DG) as a viable option for systems reinforcement. In the paper, the DG technology is considered as a possible solution for distribution systems capacity problems, along several years. Therefore, compound solutions comprising the i…
A new innovative cooling law for simulated annealing algorithms
2015
The present paper proposes an original and innovative cooling law in the field of Simulated Annealing (SA) algorithms. Particularly, such a law is based on the evolution of different initial seeds on which the algorithm works in parallel. The efficiency control of the new proposal, executed on problems of different kind, shows that the convergence quickness by using such a new cooling law is considerably greater than that obtained by traditional laws. Furthermore, it is shown that the effectiveness of the SA algorithm arising from the proposed cooling law is independent of the problem type. This last feature reduces the number of parameters to be initially fixed, so simplifying the prelimin…
A polynomial algorithm solving a special class of hybrid optimal control problems
2006
Hybrid optimal control problems are, in general, difficult to solve. A current research goal is to isolate those problems that lead to tractable solutions [5]. In this paper, we identify a special class of hybrid optimal control problems which are easy to solve. We do this by using a paradigm borrowed from the Operations Research field. As main result, we present a solution algorithm that converges to the exact solution in polynomial time. Our approach consists in approximating the hybrid optimal control problem via an integer-linear programming reformulation. The integer-linear programming problem is a Set-covering one with a totally unimodular constraint matrix and therefore solving the S…
Multi-step ahead electricity price forecasting using a hybrid model based on two-layer decomposition technique and BP neural network optimized by fir…
2017
In the deregulated competitive electricity market, the price which reflects the relationship between electricity supply and demand is one of the most important elements, making it crucial for all market participants to precisely forecast the electricity price. However, electricity price series usually has complex features such as non-linearity, non-stationarity and volatility, which makes the price forecasting turn out to be very difficult. In order to improve the accuracy of electricity price forecasting, this paper first proposes a two-layer decomposition technique and then develops a hybrid model based on fast ensemble empirical mode decomposition (FEEMD), variational mode decomposition …
Multi-Objective Design of Optimisation of a Class of PKMs - The 3-DOF Gantry-Tau
2010
The main contribution of this paper is the use of the evolutionary multi-objective methodology based on the com plex search algorithm and geometric approaches to optimise a parallel kinematic structure. The design optimisation scheme includes the kinematic (collisions free workspace), elastostatic (Cartesian stiffness in the Y direction) and elastodynamic (first resonance frequency) properties of the PKM as the objectives. The optimisation constraints are the support frame lengths, actuator positions, end-effector’s kinematic parameters and the robot’s arm lengths. The optimisation results are presented in this paper.
The Scatter Search Methodology
2011
Scatter search (SS) is an evolutionary approach for optimization. It has been applied to problems with continuous and discrete variables and with a single or multiple objectives. The success of SS as an optimization technique is well documented in a constantly growing number of journal articles and book chapters. This article first focuses on the basic SS framework, which is responsible for most of the outcomes reported in the literature, and then covers advanced elements that have been introduced in a few selected papers, such as the hybridization with tabu search, a well-known memory-based metaheuristic. We consider the maximum diversity problem to illustrate the search elements, methods …