Search results for "Genetic algorithm"
showing 10 items of 834 documents
On the Use of Prognostics and Health Management to Jointly Schedule Production and Maintenance on a Single Multi-purpose Machine
2020
This paper address the problem of using prognostic information in the decision-making process of a single multi-purpose machine. The prognostics and health management method is compared to condition-based maintenance combined with a genetic algorithm to determine the joint schedule of maintenance and production. The paper presents a methodology to select the adequate strategy while considering several factors that influence the functioning of the machine. The results show that operational and conditions variability influence the choice of the suitable methods. In the presented case, we show configurations where prognostic information is useless or useful.
A hybrid genetic algorithm for the resource-constrained project scheduling problem
2008
Abstract In this paper we propose a Hybrid Genetic Algorithm (HGA) for the Resource-Constrained Project Scheduling Problem (RCPSP). HGA introduces several changes in the GA paradigm: a crossover operator specific for the RCPSP; a local improvement operator that is applied to all generated schedules; a new way to select the parents to be combined; and a two-phase strategy by which the second phase re-starts the evolution from a neighbour’s population of the best schedule found in the first phase. The computational results show that HGA is a fast and high quality algorithm that outperforms all state-of-the-art algorithms for the RCPSP known by the authors of this paper for the instance sets j…
Schema-Backed Visual Queries over Europeana and Other Linked Data Resources
2021
We describe and demonstrate the process of extracting a data-driven schema of the Europeana cultural heritage Linked data resource (with actual data classes, properties and their connections, and cardinalities) and application of the extracted schema to create a visual query environment over Europeana. The extracted schema information allows generating SHACL data shapes describing the actual data endpoint structure. The schema extraction process can be applied also to other data endpoints with a moderate data schema size and a potentially large data triple count, as e.g., British National Bibliography Linked data resource.
A General Frame for Building Optimal Multiple SVM Kernels
2012
The aim of this paper is to define a general frame for building optimal multiple SVM kernels. Our scheme follows 5 steps: formal representation of the multiple kernels, structural representation, choice of genetic algorithm, SVM algorithm, and model evaluation. The computation of the optimal parameter values of SVM kernels is performed using an evolutionary method based on the SVM algorithm for evaluation of the quality of chromosomes. After the multiple kernel is found by the genetic algorithm we apply cross validation method for estimating the performance of our predictive model. We implemented and compared many hybrid methods derived from this scheme. Improved co-mutation operators are u…
Embedding Evolution in Epidemic-Style Forwarding
2007
International audience; In this work, we introduce a framework to let forwarding schemes evolve in order to adapt to changing and a priori unknown environments. The framework is inspired by genetic algorithms: at each node a genotype describes the forwarding scheme used, a selection process fosters the diffusion of the fittest genotypes in the system and new genotypes are created by combining existing ones or applying random changes. A case study implementation is presented and its performance evaluated via numerical simulations.
A hybrid multi-objective optimization algorithm for content based image retrieval
2013
Abstract Relevance feedback methods in CBIR (Content Based Image Retrieval) iteratively use relevance information from the user to search the space for other relevant samples. As several regions of interest may be scattered through the space, an effective search algorithm should balance the exploration of the space to find new potential regions of interest and the exploitation of areas around samples which are known relevant. However, many algorithms concentrate the search on areas which are close to the images that the user has marked as relevant, according to a distance function in the (possibly deformed) multidimensional feature space. This maximizes the number of relevant images retriev…
Assessment of wastewater treatment alternatives for small communities: An analytic network process approach
2015
The selection of the most appropriate wastewater treatment (WWT) technology is a complex problem since many alternatives are available and many criteria are involved in the decision-making process. To deal with this challenge, the analytic network process (ANP) is applied for the first time to rank a set of seven WWT technology set-ups for secondary treatment in small communities. A major advantage of ANP is that it incorporates interdependent relationships between elements. Results illustrated that extensive technologies, constructed wetlands and pond systems are the most preferred alternatives by WWT experts. The sensitivity analysis performed verified that the ranking of WWT alternatives…
Unemployment and Migration: Does Moving Help?
2002
Abstract The migration behaviour of the unemployed in Finland is analysed in terms of the causal effectof moving on individual employment status. In 1994, 17 percent of the labour force wasunemployed and the unemployment rate exhibited a very slow decline in 1994–1996. Overhalf of those who were unemployed at the end of 1994 were still unemployed two years later.The propensity to find a job is somewhat greater among migrants. However, the positive effectof moving diminishes once other personal characteristics are accounted for. Moreover, whencontrolling for endogenous migrant selectivity, an insignificant or even negative effect onemployment status emerges. This indicates that the relatively …
Complexity Selection of the Self-Organizing Map
2002
This paper describes how the complexity of the Self-Organizing Map can be selected using the Minimum Message Length principle. The use of the method in textual data analysis is also demonstrated.
On the Optimization of Self-Organizing Maps by Genetic Algorithms
1999
Publisher Summary This chapter reviews the research on the genetic optimization of self-organizing maps (SOMs). The optimization of learning rule parameters and of initial weights is able to improve network performance. The latter, however, requires chromosome sizes proportional to the size of the SOM and becomes unwieldy for large networks. The optimization of learning rule structures leads to self-organization processes of character similar to the standard learning rule. A particularly strong potential lies in the optimization of SOM topologies, which allows the study of global dynamical properties of SOMs and related models, as well as to develop tools for their analysis. Hierarchies of …