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Examining the relationship between algorithm stopping criteria and performance using elitist genetic algorithm

Jin-Lee Kim
2010 Proceedings of the 2010 Winter Simulation Conference  
Thus, it is necessary to identify the tradeoff between the algorithm stopping criteria and the algorithm performance.  ...  Elitist genetic algorithm is used to solve 30 projects having 30-Activity with four renewable resources for statistical analysis.  ...  Figure 2: Average algorithm runtimes in millisecond for 30 projects For the comparison test of the difference among the means of algorithm runtimes by stopping criteria, one-way analysis of variance is  ... 
doi:10.1109/wsc.2010.5679014 dblp:conf/wsc/Kim10a fatcat:gx4yjhpaxfbjpl2bqginms5o6i

Optimal stopping time of compact genetic algorithm on deceptive problem using real options analysis

Sunisa Rimcharoen, Daricha Sutivong, Prabhas Chongstitvatana
2007 2007 IEEE Congress on Evolutionary Computation  
algorithm on the trap problem.  ...  This paper proposes using a decision contour derived from real options analysis, which is an evaluation tool for investment under uncertainty, to suggest an optimal stopping time of the compact genetic  ...  The proposed criterion is different from few theoretical stopping criteria of the genetic algorithms in the literature.  ... 
doi:10.1109/cec.2007.4425084 dblp:conf/cec/RimcharoenSC07 fatcat:xnlbyjrzlndjzhxhk4a7t23a7i

The saturation of population fitness as a stopping criterion in genetic algorithm

Fong Foo Yeng, Soo Kum Yoke, Azrina Suhaimi
2019 International Journal of Electrical and Computer Engineering (IJECE)  
Genetic Algorithm is an algorithm imitating the natural evolution process in solving optimization problems.  ...  The proposed stopping criteria was compared with conventional stopping criterion, fittest chromosomes repetition, under various parameters setting.  ...  Section 3 details hybrid algorithms for two tested models, one with conventional stopping criterion, one with the proposed stopping criterion.  ... 
doi:10.11591/ijece.v9i5.pp4130-4137 fatcat:inm5mkpfuvagrfpxg2eodibsyy

The Relationship between Metaheuristics Stopping Criteria and Performances

Mohamed-Mahmoud Ould Sidi, Bénédicte Quilot-Turion, Abdeslam Kadrani, Michel Génard, Françoise Lescourret
2014 International Journal of Applied Metaheuristic Computing  
This paper addresses this issue using the Non-dominated Sorting Genetic Algorithm (NSGA-II) and the Multi-Objective Particle Swarm Optimization with Crowding Distance (MOPSO-CD) for the model-based design  ...  Indeed, it is difficult to find the best compromise between the stopping criterion and the algorithm performance.  ...  Meta-Heuristics Optimization Algorithms in Engineering, metaheuristics-stopping-criteria-and- performances/117266?  ... 
doi:10.4018/ijamc.2014070104 fatcat:l4vucmukfzbfrle436es3d477a

Hybrid Optimisation Method Using PGA and SQP Algorithm

B. T. Skinner, H. T. Nguyen, D. K. Liu
2007 2007 IEEE Symposium on Foundations of Computational Intelligence  
This paper investigates the hybridisation of two very different optimisation methods, namely the Parallel Genetic Algorithm (PGA) and Sequential Quadratic Programming (SQP) Algorithm.  ...  Experiments show the hybrid method effectively combines the robust and global search property of Parallel Genetic Algorithms with the high convergence velocity of the Sequential Quadratic Programming Algorithm  ...  The RFSQP algorithm halts once stopping criteria has been fulfilled.  ... 
doi:10.1109/foci.2007.372150 dblp:conf/foci/SkinnerNL07 fatcat:z6wjpafhgvctrdveqhyskhrd4e

Determining Optimal Breakpoints in Urban Power Networks with Genetic Algorithm

S.E. Kokin, S.A. Dmitriev, A.I. Halyasmaa
2012 The Renewable Energies and Power Quality Journal (RE&PQJ)  
Determining the optimal breakpoints is a complicated discrete task, for which the method of genetic algorithm becomes the most suitable solution.  ...  Devising Genetic Algorithm for Determining Optimal Breakpoints.  ...  population for the present iteration of the genetic algorithm.  ... 
doi:10.24084/repqj10.554 fatcat:r3f22z2vobcmrmmm6o47tx2vg4

ANN-Based Stop Criteria for a Genetic Algorithm Applied to Air Impingement Design

Sánchez-Chica, Zulueta, Teso-Fz-Betoño, Martínez-Filgueira, Fernandez-Gamiz
2019 Energies  
The performance of this ANN is used as a stop criterion for the optimization process.  ...  The ANN is trained with the points obtained during an optimization process by a genetic algorithm and a flower pollination algorithm.  ...  Parameters Genetic Algorithm Genetic Algorithm with Stop Criteria Mean best Cost 33.81 33.68 Standard deviation of best Cost 0.08 0.01 Mean temperature 31.66 °C 31.42 Std of temperature 0.17  ... 
doi:10.3390/en13010016 fatcat:ku3jtueztnhw3n2xft5pwdoayq

A Permutation Encoding Technique Applied to Genetic Algorithm Solution of Resource Constrained Project Scheduling Problem

MH Oladeinde, CA Oladeinde
2014 Nigerian Journal of Technology  
Figure 7 : 7 Arrow diagram of Project Network (Udosen, 1997) Figure 9 :Figure 10 : 910 Solution obtained using GA for stopping criteria of 13 generations Solution obtained using Genetic Algorithm for  ...  stopping criteria of 40 generations 14.  ... 
doi:10.4314/njt.v34i1.16 fatcat:z5s2h2fhxvejpbs326ogyyhx6a

Analysis of the optimality of the standard genetic code

Balaji Kumar, Supreet Saini
2016 Molecular Biosystems  
On left, ability of genetic codes to encode additional information and their robustness to frameshift mutations.  ...  Many theories have been proposed attempting to explain the origin of the genetic code. In this work, we compare performance of the standard genetic code against millions of randomly generated codes.  ...  algorithm to score genetic codes for their ability to minimize frameshift errors (See methods).  ... 
doi:10.1039/c6mb00262e pmid:27327359 fatcat:qxvxoewmkne5xis3ut6taz34pi

Regression Testing based on Genetic Algorithms

Esha Khanna
2016 International Journal of Computer Applications  
The work proposes a genetic algorithm based prioritization technique, which intelligently reorders the test cases on maximum fault detection rate.  ...  The work paves the way of genetic algorithms in regression testing.  ...  Stopping conditions for GA are maximum generations, Elapsed time and unchanged fitness [21] . PROPOSED WORK The work proposes use of genetic algorithm in regression testing.  ... 
doi:10.5120/ijca2016912201 fatcat:ffgeafodv5dfnksk5azwfq7qie

A Genetic algorithm to solve the container storage space allocation problem [article]

I. Ayachi : LACS, Ecole Nationale des Ingenieurs de Tunis
2013 arXiv   pre-print
This paper presented a genetic algorithm (GA) to solve the container storage problem in the port.  ...  In this paper, an adaptation of the genetic algorithm to the container storage problem is detailed and some experimental results are presented and discussed.  ...  To evaluate the results of the proposed genetic algorithm, the influence of the container type number, the stopping criteria and the population size are studied. A.  ... 
arXiv:1303.1051v1 fatcat:ds5reb66zzdl3kcyqnrcdbzc5m


François-Joseph Lapointe
2005 Proceedings of the 2005 workshops on Genetic and evolutionary computation - GECCO '05  
In this paper, a genetic algorithm is introduced to generate variants of a choreographic sequence, which are then selected using different criteria.  ...  The mutation phase of the algorithm applies six types of mutations on single sequences, as well as four types of mutations on multiple sequences.  ...  For one, a grammar-based genetic programming system may be defined to encode the rules of a particular type of dance.  ... 
doi:10.1145/1102256.1102338 dblp:conf/gecco/Lapointe05 fatcat:h6twi64nwfbmlj4l6ofjzjtgwi

Optimization Study For The Cross-Section Of A Concrete Gravity Dam: Genetic Algorithm Model And Application

L. Araujo, A. Vieira, D. Gutstein
2019 Revista Internacional de Métodos Numéricos para Cálculo y Diseño en Ingeniería  
This study focuses on the shape optimization of concrete gravity dams using genetic algorithms.  ...  The optimum cross-section of a concrete gravity dam is achieved by the Genetic Algorithm (GA) through a Matlab routine developed by the author.  ...  The algorithm stops when one of the stopping criteria is met. Figure 5 shown the convergence process. The GA parameters of Optdam program are shown in Table 1 .  ... 
doi:10.23967/j.rimni.2019.06.002 fatcat:dretnyjvnff2jlxmshusbr65yu

Dynamic Process Scheduling and Sequencing Using Genetic Algorithm

Priyanka Rani, Shakti Nagpal
2014 IOSR Journal of Computer Engineering  
This paper present the implementation of genetic algorithm for operating system process scheduling.  ...  The scheduling is considered as NP hard problem .In this paper, we use the power of genetic algorithm to provide the efficient process scheduling.  ...  Is done=Optimization criteria met? Step 10. If (not) then, i=i+1.[increase iteration number]. END FOR[If optimization criteria met, stop the algorithm]. Step 11. Output the best solution END GA G.  ... 
doi:10.9790/0661-16394853 fatcat:w2j2zaczcfdl7cwh5sltl656cu

Minimizing total flowtime and maximum earliness on a single machine using multiple measures of fitness

Mary E. Kurz, Sarah Canterbury
2005 Proceedings of the 2005 conference on Genetic and evolutionary computation - GECCO '05  
The intent of this research is to investigate methods to use genetic algorithms to find the set of efficient solutions to a bi-criteria problem.  ...  We investigate its performance on a specific bi-criteria scheduling problem, minimizing total flowtime and maximum earliness on a single machine.  ...  We begin with a brief review of genetic algorithms and describe the random keys genetic algorithm (RKGA) in Section 2. In Section 3, we introduce a bi-criteria RKGA, BRKGA.  ... 
doi:10.1145/1068009.1068144 dblp:conf/gecco/KurzC05 fatcat:5jnkdrzvcbhrbftxeelwofucfi
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