Search results for "Evolution strategy"
showing 9 items of 9 documents
Memetic Algorithms in Engineering and Design
2012
When dealing with real-world applications, one often faces non-linear and nondifferentiable optimization problems which do not allow the employment of exact methods. In addition, as highlighted in [104], popular local search methods (e.g. Hooke-Jeeves, Nelder Mead and Rosenbrock) can be ill-suited when the real-world problem is characterized by a complex and highly multi-modal fitness landscape since they tend to converge to local optima. In these situations, population based meta-heuristics can be a reasonable choice, since they have a good potential in detecting high quality solutions. For these reasons, meta-heuristics, such as Genetic Algorithms (GAs), Evolution Strategy (ES), Particle …
Evolving non-dominated solutions in multiobjective service restoration for automated distribution networks
2001
Abstract The problem here dealt with is that of Service Restoration (SR) in automated distribution networks. In such networks, configuration and compensation level as well as loads insertion status can be remotely controlled. The considered SR problem should be handled using Multiobjective Optimization, MO, techniques since its solution requires a compromise between different criteria. In the adopted formulation, these criteria are the supply of the highest number of loads and the minimum power losses. The Authors propose a new MO approach, the Non-dominated Sorting Fuzzy Evolution Strategy, NS_FES, which uses part of the Non-dominated Sorting Genetic Algorithm, NSGA, proposed by K. Deb. Th…
On multi-objective optimal reconfiguration of MV networks in presence of different grounding
2015
The present work faces the traditional multi-objective optimal reconfiguration problem of a distribution grid including the safety issue in the objective functions. Actually, in many medium voltage networks still transformers with ungrounded neutral and with resonant grounded neutral coexist in the same area. This may be sometimes cause of problems during a single-line-to-ground fault if the ground electrodes of one or more cabins, initially designed for satisfying the safety conditions in a resonant grounded neutral network, after the reconfiguration are in a grounded neutral one or vice versa. In the paper a safety objective function is defined and the Non dominated Sorting Genetic Algori…
A Study of the Coevolution of Digital Organisms with an Evolutionary Cellular Automaton
2021
This article belongs to the Section Evolutionary Biology.
Multiobjective service restoration in distribution networks using an evolutionary approach and fuzzy sets
2000
Abstract In this article, the service restoration (SR) problem in electrical distribution networks is dealt with using an evolutionary strategy (ES) with a fuzzy definition of the conflicting objectives. The normal operation status allows the remote control of tie-switches, of capacitor banks and load connection. When a permanent fault occurs, the same remote control actions can be performed with the aim of restoring the service in the concerned areas. The status of these remotely controllable elements is the boolean optimisation variables for the SR problem. Besides this, here the SR problem is dealt with in a multiple objectives (MO) formulation. Indeed, the power losses’ term is consider…
Evolutionary algorithm for fiber laser in ultrashort pulse regime
2016
This thesis deals with the generation of ultrashort pulses within a fiber laser cavity through the automatic optimization of its parameters by an evolutionary algorithm. The interest of this subject comes from the difficulty to systematically explore dynamics in a large domain of experimental parameters. We have shown that it is possible to implement an evolutionary algorithm on fiber laser cavity with appropriate precautions. We have experimentally demonstrated for the first time the mode locking of a laser cavity only using the optimization of polarization controllers through an automatic and self-learning procedure. We also have demonstrated that selecting the mode locking from it radio-…
ISEBA – A Framework for IS Evolution Benefit Assessment
2005
Decisions regarding information system evolution strategy, including modernization or replacement, are economically significant. Selection of a proper method for analyzing potential options, acquisition of suitable metrics or follow-up data, and evaluation of the results are major challenges in the evolution strategy decision making. In order to address these challenges, a framework for Information System Evolution Benefit Assessment (ISEBA) was developed. ISEBA provides assistance in the selection of a benefit-evaluation method for the investment situation at hand. It is based on empirical research on industrial decision making and co-operation projects, and examination of existing researc…
Shakedown optimal design of reinforced concrete structures by evolution strategies
2000
Approaches the shakedown optimal design of reinforced concrete (RC) structures, subjected to variable and repeated external quasi‐static actions which may generate the well‐known shakedown or adaptation phenomenon, when constraints are imposed on deflection and/or deformation parameters, in order to simulate the limited flexural ductility of the material, in the presence of combined axial stress and bending. Within this context, the classical shakedown optimal design problem is revisited, using a weak upper bound theorem on the effective plastic deformations. For this problem a new computational algorithm, termed evolution strategy, is herein presented. This algorithm, derived from analogy …
A hybrid evolution strategy for the open vehicle routing problem
2010
This paper presents a hybrid evolution strategy (ES) for solving the open vehicle routing problem (OVRP), which is a well-known combinatorial optimization problem that addresses the service of a set of customers using a homogeneous fleet of non-depot returning capacitated vehicles. The objective is to minimize the fleet size and the distance traveled. The proposed solution method manipulates a population of @m individuals using a (@m+@l)-ES; at each generation, a new intermediate population of @l offspring is produced via mutation, using arcs extracted from parent individuals. The selection and combination of arcs is dictated by a vector of strategy parameters. A multi-parent recombination …