Determination of the Kinetic Constants of a Chemical Reaction in Heterogeneous Phase Using Parameterized Metaheuristics

Cutillas-Lozano, José-Matías; Giménez, Domingo

doi:10.1016/j.procs.2013.05.243

Cited by 8 publications

(5 citation statements)

References 8 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Instances of the parameters corresponding to the four basic metaheuristics considered have been chosen. In previous works [4,5] we have experimented in depth with hybrid metaheuristics to obtain the most efficient one for the problems PECEW and PKICO. Therefore, it also seems appropriate to compare the best results obtained with the best hybrid metaheuristic for those problems with those obtained with the hyperheuristic, which is applied here for the first time to MDP, for which the results with the hyperheuristic are compared with those of basic metaheuristics.…”

Section: Resultsmentioning

confidence: 99%

“…Therefore, it also seems appropriate to compare the best results obtained with the best hybrid metaheuristic for those problems with those obtained with the hyperheuristic, which is applied here for the first time to MDP, for which the results with the hyperheuristic are compared with those of basic metaheuristics. Table 2 shows the values selected for the parameters for the four basic metaheuristics and the best hybrid metaheuristics (combinations of the four pure metaheuristics) obtained for PECEW in [5] (Mhy1) and for PKICO in [4] (Mhy2). The best hybrid metaheuristic for MDP (Mhy3) has also been considered.…”

Section: Resultsmentioning

confidence: 99%

“…The first and second problems were optimized by applying the metaheuristic scheme [4,5], so the results with the application of the hyperheuristic approach introduced here can be compared with earlier results in which the metaheuristics are tuned with the parametrized scheme. Furthermore, MDP is a widely studied problem, and the application of our hyperheuristic approach to this problem allows us to compare the results with those of well established metaheuristics.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Hyperheuristics Based on Parametrized Metaheuristic Schemes

Cutillas-Lozano

Giménez

Almeida

2015

Proceedings of the 2015 Annual Conference on Genetic and Evolutionary Computation

Self Cite

View full text Add to dashboard Cite

The use of a unified parametrized scheme for metaheuristics facilitates the development of metaheuristics and their application. The unified scheme can also be used to implement hyperheuristics on top of parametrized metaheuristics, selecting appropriate values for the metaheuristic parameters, and consequently the metaheuristic itself. The applicability of hyperheuristics to efficiently solve computational search problems is tested with the application of local and global search methods (GRASP, Tabu Search, Genetic algorithms and Scatter Search) and their combinations to three problems: a problem of optimization of power consumption in operation of wells, the determination of the kinetic constants of a chemical reaction and the maximum diversity problem. The hyperheuristic approach provides satisfactory values for the metaheuristic parameters and consequently satisfactory metaheuristics.

show abstract

Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Hyperheuristics Based on Parametrized Metaheuristic Schemes

Cutillas-Lozano

Giménez

Almeida

2015

Proceedings of the 2015 Annual Conference on Genetic and Evolutionary Computation

Self Cite

View full text Add to dashboard Cite

show abstract

“…metaheuristic parameters (ParamXXX in Algorithm 1), in each of these functions to provide a wider range of metaheuristics. Cutillas-Lozano et al (2012); Almeida et al (2013) and Cutillas-Lozano and Giménez (2013) show that the use of a parameterized schema of metaheuristics helps to find satisfactory metaheuristics and to tune them for a particular problem. Several metaheuristics could be evaluated for the problem (each with its corresponding tuning process), and hybrid metaheuristic schemes can also be considered.…”

Section: Metaheuristics For Virtual Screening On Heterogeneous Systemsmentioning

confidence: 99%

METADOCK: A parallel metaheuristic schema for virtual screening methods

Imbernón

Cecilia

Pérez‐Sánchez

et al. 2017

The International Journal of High Performance Computing Applica

Self Cite

View full text Add to dashboard Cite

Virtual screening through molecular docking can be translated into an optimization problem, which can be tackled with metaheuristic methods. The interaction between two chemical compounds (typically a protein, enzyme or receptor, and a small molecule, or ligand) is calculated by using highly computationally demanding scoring functions that are computed at several binding spots located throughout the protein surface. This paper introduces METADOCK, a novel molecular docking methodology based on parameterized and parallel metaheuristics and designed to leverage heterogeneous computers based on heterogeneous architectures. The application decides the optimization technique at running time by setting a configuration schema. Our proposed solution finds a good workload balance via dynamic assignment of jobs to heterogeneous resources which perform independent metaheuristic executions when computing different molecular interactions required by the scoring functions in use. A cooperative scheduling of jobs optimizes the quality of the solution and the overall performance of the simulation, so opening a new path for further developments of virtual screening methods on high-performance contemporary heterogeneous platforms.

show abstract

“…For example, DNA analysis applies the method to find out the sequence of chains. A tuning process is necessary to select the metaheuristics to minimize the computational cost [5][6][7][8][9].…”

Section: Introductionmentioning

confidence: 99%

Metaheuristics Based Optimization Technique for Protein-Ligand Docking

K*¹,

Balaji²

2019

IJRTE

View full text Add to dashboard Cite

Virtual screening using molecular docking requires optimization, which can be solved by using metaheuristics methods. Typically the interaction between two compounds is calculated using computationally intensive Scoring Functions (SF) which is computed in several spots which are called as binding surfaces. In this paper we present a novel approach for molecular docking which is based on parameterized and parallel metaheuristics which is useful in leveraging heterogeneous computing based on heterogeneous architectures. The approach decides on the optimization technique at running time by setting up a new configuration schema that allows parallel offloading of the data intensive sections of the docking. Hence the docking process is carried out in parallel efficiently while performing the metaheuristics execution. The approach carries out docking and computations of molecular interactions required for SF in parallel so that the time efficiency is improved. This opens a new path for further developments in virtual screening methods in heterogeneous platform.

show abstract

Determination of the Kinetic Constants of a Chemical Reaction in Heterogeneous Phase Using Parameterized Metaheuristics

Cited by 8 publications

References 8 publications

Hyperheuristics Based on Parametrized Metaheuristic Schemes

Hyperheuristics Based on Parametrized Metaheuristic Schemes

METADOCK: A parallel metaheuristic schema for virtual screening methods

Metaheuristics Based Optimization Technique for Protein-Ligand Docking

Contact Info

Product

Resources

About