Search results for " annealing"
showing 10 items of 95 documents
The egoistic approach to parallel process migration into heterogeneous workstation network
1996
Abstract A new approach to the allocation of processes in a distributed system is discussed. The proposed solution deals with process migration into heterogeneous systems by means of a strategy that delegates the individual parallel applications to manage the migration of their processes by themselves, on the basis of their own performance objectives. This approach is discussed in opposition to the global scheduling based one, and the load balancing objective is pursued as an effect of the optimization of individual applications. A new performance evaluation criterion is introduced that consists in monitoring the delays that occur when two parallel processes run towards a common synchroniza…
Improved SOM Learning using Simulated Annealing
2007
Self-Organizing Map (SOM) algorithm has been extensively used for analysis and classification problems. For this kind of problems, datasets become more and more large and it is necessary to speed up the SOM learning. In this paper we present an application of the Simulated Annealing (SA) procedure to the SOM learning algorithm. The goal of the algorithm is to obtain fast learning and better performance in terms of matching of input data and regularity of the obtained map. An advantage of the proposed technique is that it preserves the simplicity of the basic algorithm. Several tests, carried out on different large datasets, demonstrate the effectiveness of the proposed algorithm in comparis…
A comparison of simplex and simulated annealing for optimization of a new rear underrun protective device
2012
In this paper, two optimization approaches to improve the product design process have been analysed. Through the analysis of a case study, concerning the designing of a new High Energy Absorption Rear Underrun Protective Device (HEARUPD), two different optimization approaches (simplex and simulated annealing) have been compared. In the implemented optimization processes, the crash between an economy car and the rear part of a truck has been simulated by dynamic numerical (FEM) analyses. Moreover, authors have proposed the use of a suitable linear function of four variables with the purpose of reducing the multi-objective optimization processes to mono-objective ones. That has been made to s…
Modelling the Frequency of Interarrival Times and Rainfall Depths with the Poisson Hurwitz-Lerch Zeta Distribution
2022
The Poisson-stopped sum of the Hurwitz–Lerch zeta distribution is proposed as a model for interarrival times and rainfall depths. Theoretical properties and characterizations are investigated in comparison with other two models implemented to perform the same task: the Hurwitz–Lerch zeta distribution and the one inflated Hurwitz–Lerch zeta distribution. Within this framework, the capability of these three distributions to fit the main statistical features of rainfall time series was tested on a dataset never previously considered in the literature and chosen in order to represent very different climates from the rainfall characteristics point of view. The results address t…
Influence of rounding errors on the quality of heuristic optimization algorithms
2011
Abstract Search space smoothing and related heuristic optimization algorithms provide an alternative approach to simulated annealing and its variants: while simulated annealing traverses barriers in the energy landscape at finite temperatures, search space smoothing intends to remove these barriers, so that a greedy algorithm is sufficient to find the global minimum. Several formulas for smoothing the energy landscape have already been applied, one of them making use of the finite numerical precision on a computer. In this paper, we thoroughly investigate the effect of finite numerical accuracy on the quality of results achieved with heuristic optimization algorithms. We present computation…
Investigation of acceptance simulated annealing — A simplified approach to adaptive cooling schedules
2010
Abstract Simulated annealing is the classic physical optimization algorithm, which has been applied to a large variety of problems for many years. Over time, several adaptive mechanisms for decreasing the temperature and thus controlling the acceptance of deteriorations have been developed, based on the measurement of the mean value and the variance of the energy. Here we propose a new simplified approach in which we consider the probability of accepting deteriorations as the main control parameter and derive the temperature by averaging over the last few deteriorations stored in a memory. We present results for the traveling salesman problem and demonstrate, how the amount of data retained…
HOW SMART DOES AN AGENT NEED TO BE?
2005
The classic distributed computation is done by atoms, molecules or spins in vast numbers, each equipped with nothing more than the knowledge of their immediate neighborhood and the rules of statistical mechanics. These agents, 1023 or more, are able to form liquids and solids from gases, realize extremely complex ordered states, such as liquid crystals, and even decode encrypted messages. We will describe a study done for a sensor-array "challenge problem" in which we have based our approach on old-fashioned simulated annealing to accomplish target acquisition and tracking under the rules of statistical mechanics. We believe the many additional constraints that occur in the real problem ca…
Multilayer neural networks: an experimental evaluation of on-line training methods
2004
Artificial neural networks (ANN) are inspired by the structure of biological neural networks and their ability to integrate knowledge and learning. In ANN training, the objective is to minimize the error over the training set. The most popular method for training these networks is back propagation, a gradient descent technique. Other non-linear optimization methods such as conjugate directions set or conjugate gradient have also been used for this purpose. Recently, metaheuristics such as simulated annealing, genetic algorithms or tabu search have been also adapted to this context.There are situations in which the necessary training data are being generated in real time and, an extensive tr…
Different Methods of Artificial Intelligence Used for Optimization the Turning Process
2015
In this paper, we realize a comparative study between some heuristics methods applied in turning operation in order to find optimal cutting parameters. We consider five different constraints aimed to achieve minimum total cost of machining. We have chosen the Simulated Annealing (SA) – a local search method, and Weighted-Sum Genetic Algorithm (WSGA) – a non-Pareto approach of a multi-objective optimization algorithm, based on a weighted aggregation of objectives. The aggregation may be with fixed weights or with random (variable) weights. The simulations showed that, even if it produces better results than the SA, WSGA with fixed weights, does not lead to optimum results, highlighting in th…
Vehicle routing problems with drones equipped with multi-package payload compartments
2022
The vehicle routing problem with drones (VRP-D) consists of designing combined truck-drone routes and schedules to serve a set of customers with specific requests and time constraints. In this paper, VRP-D is extended to include a fleet of drones equipped with multi-package payload compartments to serve more customers on a single trip. Moreover, a drone can return to a truck, different from the one from which it started, to swap its depleted battery and/or to pick up more packages. This problem, denoted as VRP-D equipped with multi-package payload compartments (VRP-D-MC), aims to maximize total profit. In this work, an adaptive multi-start simulated annealing (AMS-SA) metaheuristic algorith…