Performance and parameterization of the algorithm Simplified Generalized Simulated Annealing

Júnior, Alcino Dall'Igna; Silva, Renato S.; Mundim, Kleber C.; Dardenne, Laurent E.

doi:10.1590/s1415-47572004000400024

Cited by 17 publications

(10 citation statements)

References 26 publications

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“…⌬ t,i computed this way is not limited. Thus, we use a simplification on this equation, introduced by Dall'Igna et al, 19 where ⌬ t,i is now given by this own function, and not by its inverse. We consider…”

Section: Methodsmentioning

confidence: 99%

Generalized simulated annealing applied to protein folding studies

Agostini¹,

Soares-Pinto²,

Moret³

et al. 2006

J Comput Chem

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During the last few years, computational simulations based on the atomic description of biological molecules have resulted in significant advances in the comprehension of biological processes. It is well known, however, that a molecular system may have a great number of conformations due to the large number of rotation of degrees of freedom around chemical bonds, leading to several local minima on the energy hypersurface. It has been proposed though, that proteins express their biological function when their structure is close to a conformation with energy global minimum. To help solve the protein-folding problem, we use a new strategy based on Simulated Annealing methods. These methods have been well suited for a large extent of optimization problems, especially those containing many local minima. In fact, this work applies the Generalized Simulated Annealing method (GSA) coupled to the GROMOS96 Molecular Force Field to research the minimum energy conformation of 18-alanine. We show that the q(T) GSA parameter can be used to control the freezing process during the annealing procedure, and to avoid polypeptide chains to be trapped in energy local minima. We scanned the q-values for visiting (q(V)) and accepting (q(A)) functions for q(T) values ranging from 1 to 3, and found the best values to obtain an alpha-helix conformation for the polyalanine peptide, which is the conformation with energy global minimum. Global optimization methods also exemplify a class of applications that requires a large amount of computational resources, being suitable for Grid computing. To implement a Grid computing platform, we developed and tested a Grid environment based on MYGRID middleware, which is a technology that can employ all machines accessed by the user to run the application.

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Section: Methodsmentioning

confidence: 99%

Generalized simulated annealing applied to protein folding studies

Agostini¹,

Soares-Pinto²,

Moret³

et al. 2006

J Comput Chem

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“…A common practice followed by many researches is to compare different algorithms on a large test set, especially when algorithms may suffer is the scaling problem with many orders of magnitude differences between the domain and the function hyper-surface [47], such as Goldstein-Price and Trid.…”

Section: Introductionmentioning

confidence: 99%

A literature survey of benchmark functions for global optimisation problems

Jamil

Yang

2013

IJMMNO

819

445

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Test functions are important to validate and compare the performance of optimization algorithms. There have been many test or benchmark functions reported in the literature; however, there is no standard list or set of benchmark functions. Ideally, test functions should have diverse properties so that can be truly useful to test new algorithms in an unbiased way. For this purpose, we have reviewed and compiled a rich set of 175 benchmark functions for unconstrained optimization problems with diverse properties in terms of modality, separability, and valley landscape. This is by far the most complete set of functions so far in the literature, and tt can be expected this complete set of functions can be used for validation of new optimization in the future.

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“…The TS algorithm was tuned; Tabu list of different sizes (5,7,8,9,10,11,12,15,20), were tried. Tabu-list size of 10 was found to be more effective in guiding the search.…”

Section: Methodsmentioning

confidence: 99%

Tabu Search with Explicit Adaptive Guiding Heuristic for the Examination Timetabling Problem

Ezike¹

2020

NIPES

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Tabu Search algorithm (TS) is one of the leading methods for solving the Examination Timetabling Problem (ETP). The challenge with TS which uses only one solution in searching is that it can easily miss some areas of the search space and chose the best solution based on the current search step and position without taking the future steps into consideration. To address these problems, an explicit and adaptive guiding heuristic was proposed for the standard TS algorithm with the goal of enhancing its performance. The standard TS and the TS with the explicit adaptive guiding mechanism, the TS_G algorithm were implement using the Java programing language (version 8.92) with the MySQL database and experimented with data from Bells University of Technology, Ota. Performance of the two algorithms were evaluated using first Order Conflict Counts (OCC), Second OCC and third OCC for students and invigilators respectively, in addition to memory consumption. The TS and TS_G yielded an average first OCC 0.0 and 0.0 students and 0.0 and 0.0 for invigilators. Similarly, TS and TS_G yielded average second OCC of 18.8 and 10.5 for students and, 0.0 and 0.0 for invigilators respectively. Furthermore, TS and TS_G yielded average third OCC of 33375.0 and 9922.1 for students and 0.0 and 0.0 for invigilators, respectively. The TS_G algorithm outperformed the standard TS algorithm with lower conflicts violations. Both algorithms however recorded similar memory consumption.

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Performance and parameterization of the algorithm Simplified Generalized Simulated Annealing

Cited by 17 publications

References 26 publications

Generalized simulated annealing applied to protein folding studies

Generalized simulated annealing applied to protein folding studies

A literature survey of benchmark functions for global optimisation problems

Tabu Search with Explicit Adaptive Guiding Heuristic for the Examination Timetabling Problem

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