Genetic Algorithms

TRAINING RADIAL BASIS FUNCTION NETWORKS BY GENETIC ALGORITHMS

by Juliano Mota

Publication on ICAART 2012, Vilamoura - Algarve - Portugal.

GVD AND SPM OPTIMIZATION IN OPTICAL FIBER USING A HYBRID METHOD

by Javier Fernando Botia Valderrama

Ultrashort pulses have broad bandwidth and power, which are useful to TX and RX with optical fiber. When a pulse... more Ultrashort pulses have broad bandwidth and power, which are useful to TX and RX with optical fiber. When a pulse generator is connected to SMF, dispersion and nonlinear effects can be presented such as GVD and SPM. These phenomena cause problems like decreasing the signal power and acquiring undesired frequency components. To compensate these effects, a hybrid method is proposed by means of optimal control, genetic algorithm and fuzzy clustering techniques, consequently to find the appropriated values of the parameters that allow optimizing the pulse. The results of the simulation displayed a reduction of bandwidth plus an increase in the signal amplitude, and thus both effects were mitigated.

A concept of omni-optimization for ship structural design

by Alan Klanac

Klanac, A. Jelovica, J. Advancements in Marine Structures, Guedes Soares & Das (eds), Proceedings of MARSTRUCT 2007, The 1st International Conference on Marine Structures, 12-14 March 2007, Glasgow, UK. p. 473-481. (Taylor & Francis: London).

Omni-optimization assumes a capability to perform any type of optimization, e.g. single- and multi-objective, using... more Omni-optimization assumes a capability to perform any type of optimization, e.g. single- and multi-objective, using single optimization algorithm, or the omni-optimizer. This paper addresses a novel concept for omni-optimization, by coupling vectorization with genetic algorithms (GAs). Vectorization assumes converting constraints into objectives, and their optimization alongside the original set of objectives. The GAs show excellent potential to serve as omni-optimizers, as they are a successful tool to solve both single- and multi-objective problems. This new concept is applied to structural design of the midship section of an 88m long aluminium fast ferry for the minimal hull weight and vertical centre of gravity (VCG), under multiple constraints involving structural and technological aspects and classification rules and regulations. The obtained results range up to 10 per cent for weight minimization and 6.5 per cent for VCG with the fully defined Pareto front.

Directed Evolution In Silico

by Christopher Altman

Prediction of Lignin and Extractive Content of Pinus nigra Arnold. var. Pallasiana Tree Using Near Infrared Spectroscopy and Multivariate Calibration

by ibrahim karaman

Determination of lignin and extractive content of Turkish Pine (Pinus brutia Ten.) trees using near infrared spectroscopy and multivariate calibration

by ibrahim karaman

Vector-dependent Functionally Pooled ARX Models for the Identification of Systems Under Multiple Operating Conditions

by Fotis Kopsaftopoulos

Proceedings of the 16th IFAC Symposium on System Identification, (SYSID), Brussels, Belgium, July 2012.

Capacitated Cellular Manufacturing System Design: A Genetic Algorithms Approach

by Gokhan Egilmez

Egilmez, G. and Suer, G.A., 2012, 23rd Annual POMS Conference, Chicago, Illionis, USA April 20-23, 2012 (Accepted)

Synthesis of Truss Structure Designs by NSGA-II and NodeSort Algorithm

by Mario Storga

co-authored by Stanković, Tino; Štorga, Mario; Marjanović, Dorian
published in Journal of Mechanical Engineering 58 (3) 2012, 203-212, DOI: 10.5545/sv-jme.2011.042

Paper presents a genetic algorithm based approach for synthesis of truss structure designs. Genotype represented as a... more Paper presents a genetic algorithm based approach for synthesis of truss structure designs. Genotype represented as a collection of binary encoded nodes is decoded into the phenotype by applying the NodeSort algorithm. A genotype extension to consider a cross-section as variable and variable length chromosomes to produce designs to successfully meet the boundary conditions are all being incorporated into the NodeSort to provide an efficient truss structures synthesis framework. The introduction of multi-objective optimisation using NSGA-II will help to address more real life engineering problems.

Synthesis of Truss Structure Designs by NSGA-II and NodeSort Algorithm

by Tino Stanković

Co-authored by Tino Stanković, Mario Štorga and Dorian Marjanović. Published in Journal of Mechanical Engineering 58 (3), 2012, 203-212, DOI: 10.5545/sv-jme.2011.042.

This paper presents a genetic algorithm based approach for synthesis of truss structure designs. Genotype represented... more This paper presents a genetic algorithm based approach for synthesis of truss structure designs. Genotype represented as a collection of binary encoded nodes is decoded into the phenotype by applying the NodeSort algorithm. A genotype extension to consider a cross-section as variable and variable length chromosomes to produce designs to successfully meet the boundary conditions are all being incorporated into the NodeSort to provide an efficient truss structures synthesis framework. The introduction of multi-objective optimisation using NSGA-II will help to address more real life engineering problems.

Evapotranspiration data assimilation with genetic algorithms and SWAP model for on-demand irrigation

by Baburao Kamble

Devising Adaptive Migration Policies for Cooperative Distributed Genetic Algorithms

by Ivan Ricarte

Co-authored with Edgar Noda, André Coelho, and others. Published in IEEE MSC'2002.

Distributed Genetic Algorithms (DGAs) constitute an interesting approach to undertake the premature convergence... more Distributed Genetic Algorithms (DGAs) constitute an interesting approach to undertake the premature convergence problem in evolutionary optimization. This is done by spatial partitioning a huge panmitic population into several semi-isolated groups, called demes, each evolving in parallel by its own pace, and possibly exploring different regions of the search space. At the center of such approach lies the migratory process that simulates the swapping of individuals belonging to different demes, in such a way to ensure the sharing of good genetic material. In this paper, we model the migration step in DGAs as an explicit means to promote cooperation among genetic agents, autonomous entities encapsulating GA instances for possibly tackling different sub-problems of a complicated task. The focus is on the characterization of adaptive migration policies in which the choice of what individuals to migrate and/or replace is not defined a priori but according to a more knowledge-oriented rule. Comparative results obtained for a data-mining task were conducted, in order to assess the performance of adaptive migration according to efficiency/effectiveness criteria.

Multi-objective genetic algorithm for cell formation problem considering cellular layout and operations scheduling

by Mehdi Hosseinabadi Farahani

International Journal of Computer Integrated Manufacturing
DOI:10.1080/0951192X.2012.665182

Integrated design of cellular manufacturing (CM) systems consist of three major decisions: cell formation (CF),... more Integrated design of cellular manufacturing (CM) systems consist of three major decisions: cell formation (CF), cellular layout (CL) and planning issues such as cellular scheduling (CS). This article presents a mathematical model to concurrently identify the formation of cells, cellular layout and the operations sequence with the objective of minimising total transportation cost of parts as well as minimising makespan. A multi-objective genetic algorithm (MOGA) is then developed to solve the problem. The proposed MOGA exploits a novel evolutionary process which enables it to efficiently find Pareto optimal solutions. Computational results show the advantages of the proposed integrated approach and the superiority of the proposed MOGA over some well-known multi-objective evolutionary algorithms.

2004_ACRS_srinuandee_honda_chemin_ines

by Yann Chemin

2004_afitawcca_Chemin_Honda_Ines

by Yann Chemin

2004_FOSSGRASS-GA

by Yann Chemin

2006_IEEE_TGRS_chemin_honda

by Yann Chemin

A new approach to solve a mixed-model assembly line with a bypass subline sequencing problem

by Seyed Mohammad Javad Mirzapour Al-E-Hashem

Using genetic algorithm to solve dynamic cell formation problem

by Seyed Mohammad Javad Mirzapour Al-E-Hashem

An efficient algorithm to solve a multi-objective robust aggregate production planning in an uncertain environment

by Seyed Mohammad Javad Mirzapour Al-E-Hashem