Pub Date : 2014-10-16DOI: 10.1109/NaBIC.2014.6921896
M. Medland, Kyle Robert Harrison, B. Ombuki-Berman
Traditionally, GP used a single tree-based representation which does not lend itself well to state-based programs or multiple behaviours. To alleviate this drawback, object-oriented GP (OOGP) introduced a means of evolving programs with multiple behaviours which could be easily extended to state-based programs. However, the production of programs which allowed embedded knowledge and produced readable code was still not easily addressed using the OOGP methodology. Exemplified through the evolution of graph models for complex networks, this paper demonstrates the benefits of a new approach to OOGP inspired by abstract classes and linear GP. Furthermore, the new approach to OOGP, named LinkableGP, facilitates the embedding of expert knowledge while also maintaining the benefits of OOGP.
{"title":"Demonstrating the power of object-oriented genetic programming via the inference of graph models for complex networks","authors":"M. Medland, Kyle Robert Harrison, B. Ombuki-Berman","doi":"10.1109/NaBIC.2014.6921896","DOIUrl":"https://doi.org/10.1109/NaBIC.2014.6921896","url":null,"abstract":"Traditionally, GP used a single tree-based representation which does not lend itself well to state-based programs or multiple behaviours. To alleviate this drawback, object-oriented GP (OOGP) introduced a means of evolving programs with multiple behaviours which could be easily extended to state-based programs. However, the production of programs which allowed embedded knowledge and produced readable code was still not easily addressed using the OOGP methodology. Exemplified through the evolution of graph models for complex networks, this paper demonstrates the benefits of a new approach to OOGP inspired by abstract classes and linear GP. Furthermore, the new approach to OOGP, named LinkableGP, facilitates the embedding of expert knowledge while also maintaining the benefits of OOGP.","PeriodicalId":209716,"journal":{"name":"2014 Sixth World Congress on Nature and Biologically Inspired Computing (NaBIC 2014)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2014-10-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128136465","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2014-10-16DOI: 10.1109/NaBIC.2014.6921863
Paulo Pereira, S. Leitão, E. Pires
The paper presents a study about optimal supply of the energy service, using simulations of network operation scenarios, in order to optimize resources and minimize the variables: operation cost, energy losses, generation cost and consumers shedding. These simulations create optimal operation models of the network, allowing the system operator obtain knowledge to take pre-established procedures that must be performed in situations of contingency in order to forecast and minimize drawbacks. The simulations were performed using a multiobjective particle swarm optimization algorithm. The algorithm was applied to the IEEE 14 Bus network where the optimal power flow was evaluated by the MATPOWER tool to establish an optimal electrical working model to minimize the associated costs.
{"title":"Optimal operation point in electrical grids using a MOPSO algorithm","authors":"Paulo Pereira, S. Leitão, E. Pires","doi":"10.1109/NaBIC.2014.6921863","DOIUrl":"https://doi.org/10.1109/NaBIC.2014.6921863","url":null,"abstract":"The paper presents a study about optimal supply of the energy service, using simulations of network operation scenarios, in order to optimize resources and minimize the variables: operation cost, energy losses, generation cost and consumers shedding. These simulations create optimal operation models of the network, allowing the system operator obtain knowledge to take pre-established procedures that must be performed in situations of contingency in order to forecast and minimize drawbacks. The simulations were performed using a multiobjective particle swarm optimization algorithm. The algorithm was applied to the IEEE 14 Bus network where the optimal power flow was evaluated by the MATPOWER tool to establish an optimal electrical working model to minimize the associated costs.","PeriodicalId":209716,"journal":{"name":"2014 Sixth World Congress on Nature and Biologically Inspired Computing (NaBIC 2014)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2014-10-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125061362","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2014-07-30DOI: 10.1109/NABIC.2014.6921882
O. Rocha, Paulo Vilaça, Miguel Rocha, R. Mendes
Metabolic engineering (ME) strategies have been implemented over the last few years, in order to improve microbial strains of interest in industrial biotechnology. With the advent of experimental data concerning to regulatory aspects, several efforts have been conducted to incorporate this information in genome-scale metabolic models, aiming at the improvement of phenotype simulation methods. However, most of these methods can be used only by computer science experts, since they are not available in user-friendly software ME frameworks. This work presents Reg4OptFlux, a computational framework for ME, that integrates methods for phenotype simulation and optimization strain design, relying on integrated metabolic and regulatory models. Meta-heuristic approaches such as Evolutionary Algorithms and Simulated Annealing were appropriately modified to accommodate the optimization tasks, and were applied to study the optimization of ethanol and succinic acid production using an integrated model of the E.coli host. The framework was implemented as a plug-in for OptFlux, an open-source software for ME, and it is available in the OptFlux web site (www.optflux.org).
{"title":"Reg4OptFlux: an OptFlux plug-in that comprises meta-heuristics approaches for Metabolic engineering using integrated models","authors":"O. Rocha, Paulo Vilaça, Miguel Rocha, R. Mendes","doi":"10.1109/NABIC.2014.6921882","DOIUrl":"https://doi.org/10.1109/NABIC.2014.6921882","url":null,"abstract":"Metabolic engineering (ME) strategies have been implemented over the last few years, in order to improve microbial strains of interest in industrial biotechnology. With the advent of experimental data concerning to regulatory aspects, several efforts have been conducted to incorporate this information in genome-scale metabolic models, aiming at the improvement of phenotype simulation methods. However, most of these methods can be used only by computer science experts, since they are not available in user-friendly software ME frameworks. This work presents Reg4OptFlux, a computational framework for ME, that integrates methods for phenotype simulation and optimization strain design, relying on integrated metabolic and regulatory models. Meta-heuristic approaches such as Evolutionary Algorithms and Simulated Annealing were appropriately modified to accommodate the optimization tasks, and were applied to study the optimization of ethanol and succinic acid production using an integrated model of the E.coli host. The framework was implemented as a plug-in for OptFlux, an open-source software for ME, and it is available in the OptFlux web site (www.optflux.org).","PeriodicalId":209716,"journal":{"name":"2014 Sixth World Congress on Nature and Biologically Inspired Computing (NaBIC 2014)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2014-07-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131999604","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2014-07-01DOI: 10.1109/NaBIC.2014.6921894
Diogenes Loureiro, M. Loja, Tiago A. N. Silva
Real structures can be thought as an assembly of components, as for instances plates, shells and beams. This later type of component is very commonly found in structures like frames which can involve a significant degree of complexity or as a reinforcement element of plates or shells. To obtain the desired mechanical behavior of these components or to improve their operating conditions when rehabilitating structures, one of the eventual parameters to consider for that purpose, when possible, is the location of the supports. In the present work, a beam-type structure is considered, and for a set of cases concerning different number and types of supports, as well as different load cases, the authors optimize the location of the supports in order to obtain minimum values of the maximum transverse deflection. The optimization processes are carried out using genetic algorithms. The results obtained, clearly show a good performance of the approach proposed.
{"title":"Optimal location of supports in beam structures using genetic algorithms","authors":"Diogenes Loureiro, M. Loja, Tiago A. N. Silva","doi":"10.1109/NaBIC.2014.6921894","DOIUrl":"https://doi.org/10.1109/NaBIC.2014.6921894","url":null,"abstract":"Real structures can be thought as an assembly of components, as for instances plates, shells and beams. This later type of component is very commonly found in structures like frames which can involve a significant degree of complexity or as a reinforcement element of plates or shells. To obtain the desired mechanical behavior of these components or to improve their operating conditions when rehabilitating structures, one of the eventual parameters to consider for that purpose, when possible, is the location of the supports. In the present work, a beam-type structure is considered, and for a set of cases concerning different number and types of supports, as well as different load cases, the authors optimize the location of the supports in order to obtain minimum values of the maximum transverse deflection. The optimization processes are carried out using genetic algorithms. The results obtained, clearly show a good performance of the approach proposed.","PeriodicalId":209716,"journal":{"name":"2014 Sixth World Congress on Nature and Biologically Inspired Computing (NaBIC 2014)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2014-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123170386","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2014-07-01DOI: 10.1109/NaBIC.2014.6921857
T. A. Santos, A. Galhardo
This paper presents a programable perturbation and observation control implementation for a wind generation system and its power electronic converter. The objective of the method in this particular application is to adjust the power delivered to charge a battery to its maximum and allowable value, function of the real values of several parameters and their continuous variation, the most important the wind velocity and the turbine efficiency. Also, to improve the power throughput and to use the turbine and generator marginal zones of operation, an unusual power converter is used, allowing a wide range for the input voltage values. The implemented control is continuously measuring the actual power and looks for a new and powerful operation point.
{"title":"A perturbation and observation routine used to control a power converter","authors":"T. A. Santos, A. Galhardo","doi":"10.1109/NaBIC.2014.6921857","DOIUrl":"https://doi.org/10.1109/NaBIC.2014.6921857","url":null,"abstract":"This paper presents a programable perturbation and observation control implementation for a wind generation system and its power electronic converter. The objective of the method in this particular application is to adjust the power delivered to charge a battery to its maximum and allowable value, function of the real values of several parameters and their continuous variation, the most important the wind velocity and the turbine efficiency. Also, to improve the power throughput and to use the turbine and generator marginal zones of operation, an unusual power converter is used, allowing a wide range for the input voltage values. The implemented control is continuously measuring the actual power and looks for a new and powerful operation point.","PeriodicalId":209716,"journal":{"name":"2014 Sixth World Congress on Nature and Biologically Inspired Computing (NaBIC 2014)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2014-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126646198","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2014-07-01DOI: 10.1109/NaBIC.2014.6921875
Toshihiro Suzuki, Y. Osana
In this paper, fall avoidance of bipedal walking robot is realized by the Profit Sharing that can learn deterministic policy for POMDPs environments. In this research, the Profit Sharing that can learn deterministic policy for POMDPs environments which can obtain the deterministic policy by using the history of observations is employed. We carried out a series of experiments using bipedal walking robot, and confirmed that attitude control can be realized by the Profit Sharing that can learn deterministic policy for POMDPs environments.
{"title":"Fall avoidance of bipedalwalking robot by profit sharing that can learn deterministic policy for POMDPs environments","authors":"Toshihiro Suzuki, Y. Osana","doi":"10.1109/NaBIC.2014.6921875","DOIUrl":"https://doi.org/10.1109/NaBIC.2014.6921875","url":null,"abstract":"In this paper, fall avoidance of bipedal walking robot is realized by the Profit Sharing that can learn deterministic policy for POMDPs environments. In this research, the Profit Sharing that can learn deterministic policy for POMDPs environments which can obtain the deterministic policy by using the history of observations is employed. We carried out a series of experiments using bipedal walking robot, and confirmed that attitude control can be realized by the Profit Sharing that can learn deterministic policy for POMDPs environments.","PeriodicalId":209716,"journal":{"name":"2014 Sixth World Congress on Nature and Biologically Inspired Computing (NaBIC 2014)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2014-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128893840","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2014-07-01DOI: 10.1109/NaBIC.2014.6921876
Motoki Kikuchi, Y. Osana
In this research, an automatic melody generation system considering chord progression by genetic algorithm is proposed. In the proposed automatic melody generation system, initial population are generated based on features on rhythm, pitch and chord progression of trained melody. In this system, the trained sample melody is divided into some melody blocks. Here, melody blocks mean verse, bridge, chorus and so on. And some new melodies are generated considering melody features in each block. The features on rhythm and pitch in each melody block of the sample melody are trained in some N-gram models, and they are used in order to calculate fitness in the melody generation by genetic algorithm. Some melodies are generated using the proposed system and confirmed that the proposed system can generate melodies considering features in each melody block of the trained sample melody.
{"title":"Automatic melody generation considering chord progression by genetic algorithm","authors":"Motoki Kikuchi, Y. Osana","doi":"10.1109/NaBIC.2014.6921876","DOIUrl":"https://doi.org/10.1109/NaBIC.2014.6921876","url":null,"abstract":"In this research, an automatic melody generation system considering chord progression by genetic algorithm is proposed. In the proposed automatic melody generation system, initial population are generated based on features on rhythm, pitch and chord progression of trained melody. In this system, the trained sample melody is divided into some melody blocks. Here, melody blocks mean verse, bridge, chorus and so on. And some new melodies are generated considering melody features in each block. The features on rhythm and pitch in each melody block of the sample melody are trained in some N-gram models, and they are used in order to calculate fitness in the melody generation by genetic algorithm. Some melodies are generated using the proposed system and confirmed that the proposed system can generate melodies considering features in each melody block of the trained sample melody.","PeriodicalId":209716,"journal":{"name":"2014 Sixth World Congress on Nature and Biologically Inspired Computing (NaBIC 2014)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2014-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132479040","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2014-07-01DOI: 10.1109/NaBIC.2014.6921883
Wayne Franz, P. Thulasiraman
Multi-population bio-inspired algorithms present attractive potential for hybridization because of the relatively low degree of coupling they require between groups. In this work, we present a multiple swarm particle swarm optimization (MPSO) algorithm that has been modified to incorporate populations from a genetic algorithm. We investigate the ways in which the performance of this hybrid algorithm is influenced by the topological strategy that is used to direct communication between populations. The results suggest that in addition to the topological layout, the placement of different types of swarms may indirectly affect the resulting solution quality. The hybrid algorithm with varying communication topologies is implemented on a GPU architecture.
{"title":"Effect of communication topologies on hybrid evolutionary algorithms","authors":"Wayne Franz, P. Thulasiraman","doi":"10.1109/NaBIC.2014.6921883","DOIUrl":"https://doi.org/10.1109/NaBIC.2014.6921883","url":null,"abstract":"Multi-population bio-inspired algorithms present attractive potential for hybridization because of the relatively low degree of coupling they require between groups. In this work, we present a multiple swarm particle swarm optimization (MPSO) algorithm that has been modified to incorporate populations from a genetic algorithm. We investigate the ways in which the performance of this hybrid algorithm is influenced by the topological strategy that is used to direct communication between populations. The results suggest that in addition to the topological layout, the placement of different types of swarms may indirectly affect the resulting solution quality. The hybrid algorithm with varying communication topologies is implemented on a GPU architecture.","PeriodicalId":209716,"journal":{"name":"2014 Sixth World Congress on Nature and Biologically Inspired Computing (NaBIC 2014)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2014-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123862409","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2014-07-01DOI: 10.1109/NaBIC.2014.6921888
Olayinka Idowu Oduntan, P. Thulasiraman, R. Thulasiram
The process of uncovering underlying intelligence in financial time series is non-intuitive; therefore, data analysis techniques such as clustering (i.e. grouping a collection of objects such that objects in the same group are more similar to each other than those in the other groups) are often used to extract intelligence from financial time series. In this paper, we investigate using the ant brood sorting clustering technique to extract a new form of intelligence from financial time series that can be used in diversifying portfolio composition. Brood sorting is a nature-inspired computing technique modeled after the natural phenomenon of cemetery organization and sorting of broods amongst ants. The technique reveals promising results that can be used in making informed decision on the collection of assets that can be owned together in order to minimize possible losses (in the case of a down-turn of the economy) or maximize gain (in the case of a growing economy).
{"title":"Portfolio diversification using ant brood sorting clustering","authors":"Olayinka Idowu Oduntan, P. Thulasiraman, R. Thulasiram","doi":"10.1109/NaBIC.2014.6921888","DOIUrl":"https://doi.org/10.1109/NaBIC.2014.6921888","url":null,"abstract":"The process of uncovering underlying intelligence in financial time series is non-intuitive; therefore, data analysis techniques such as clustering (i.e. grouping a collection of objects such that objects in the same group are more similar to each other than those in the other groups) are often used to extract intelligence from financial time series. In this paper, we investigate using the ant brood sorting clustering technique to extract a new form of intelligence from financial time series that can be used in diversifying portfolio composition. Brood sorting is a nature-inspired computing technique modeled after the natural phenomenon of cemetery organization and sorting of broods amongst ants. The technique reveals promising results that can be used in making informed decision on the collection of assets that can be owned together in order to minimize possible losses (in the case of a down-turn of the economy) or maximize gain (in the case of a growing economy).","PeriodicalId":209716,"journal":{"name":"2014 Sixth World Congress on Nature and Biologically Inspired Computing (NaBIC 2014)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2014-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128288939","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2014-07-01DOI: 10.1109/NaBIC.2014.6921895
A. Madureira, J. M. Santos, S. Gomes, Bruno Cunha, J. Pereira, I. Pereira
Contemporary manufacturing scheduling has still limitations in real-world environments where disturbances on working conditions could occur over time. Therefore, human intervention is required to maintain real-time adaptation and optimization and efficiently adapt to the inherent dynamic of markets. This paper addresses the problem of incorporating rush orders into the current schedule of a manufacturing shop floor organization. A set of experiments were performed in order to evaluate the applicability of supervised classification algorithms in the attempt to predict the best integration mechanism when receiving a new order in a dynamic scheduling problem.
{"title":"Manufacturing rush orders rescheduling: a supervised learning approach","authors":"A. Madureira, J. M. Santos, S. Gomes, Bruno Cunha, J. Pereira, I. Pereira","doi":"10.1109/NaBIC.2014.6921895","DOIUrl":"https://doi.org/10.1109/NaBIC.2014.6921895","url":null,"abstract":"Contemporary manufacturing scheduling has still limitations in real-world environments where disturbances on working conditions could occur over time. Therefore, human intervention is required to maintain real-time adaptation and optimization and efficiently adapt to the inherent dynamic of markets. This paper addresses the problem of incorporating rush orders into the current schedule of a manufacturing shop floor organization. A set of experiments were performed in order to evaluate the applicability of supervised classification algorithms in the attempt to predict the best integration mechanism when receiving a new order in a dynamic scheduling problem.","PeriodicalId":209716,"journal":{"name":"2014 Sixth World Congress on Nature and Biologically Inspired Computing (NaBIC 2014)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2014-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131602232","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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