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Greedy, genetic, and greedy genetic algorithms for the quadratic knapsack problem

Bryant A. Julstrom
2005 Proceedings of the 2005 conference on Genetic and evolutionary computation - GECCO '05  
The greedy heuristics do well, as does the naive GA, but the greedy GA exhibits the best performance.  ...  Two genetic algorithms encode candidate selections of objects as binary strings and generate only strings whose selections of objects have total weight no more than the knapsack's capacity.  ...  We illustrate this general observation with greedy, genetic, and greedy genetic algorithms for the Quadratic Knapsack Problem.  ... 
doi:10.1145/1068009.1068111 dblp:conf/gecco/Julstrom05a fatcat:gatoyxfifbbgjokc35dr3s6y3u

K-Means Genetic Algorithms with Greedy Genetic Operators

Lev Kazakovtsev, Ivan Rozhnov, Guzel Shkaberina, Viktor Orlov, Piotr Jdrzejowicz
2020 Mathematical Problems in Engineering  
In such cases, genetic algorithms with greedy agglomerative heuristic crossover operator might be a good choice.  ...  by the genetic algorithms for large-scale k-means problems.  ...  In Section 4, we propose new modifications to the genetic algorithms with greedy heuristic crossover operator.  ... 
doi:10.1155/2020/8839763 fatcat:qtvocyrabrhargdptp7bykoxba

Parallel Search Strategies for TSPs Using a Greedy Genetic Algorithm [chapter]

Yingzi Wei, Kanfeng Gu
2008 Greedy Algorithms  
Compared to the GA, the greedy genetic algorithm with improved genetic operations has been presented for the global optimization of TSPs.  ...  In the next a few sections, we present the greedy genetic algorithm (GGA), how we modify a genetic algorithm to solve TSP, our methodology, results, and conclusions.  ...  Parallel Search Strategies for TSPs Using a Greedy Genetic Algorithm, Greedy Algorithms, Witold Bednorz (Ed.), ISBN: 978-953-7619-27-5, InTech, Available from: http://www.intechopen.com/books/greedy_algorithms  ... 
doi:10.5772/6342 fatcat:fkal6ltzg5gzpamubunpxe6gsm

Greedy genetic algorithm to Bounded Knapsack Problem

Sarsij Kaystha, Suneeta Agarwal
2010 2010 3rd International Conference on Computer Science and Information Technology  
GREEDY GENETIC ALGORITHM (GGA) The basic idea of the flow of genetic algorithm for the bounded knapsack is shown in Figure 1 . A Greedy operator is used to ensure the feasibility of the solution.  ...  The selection operator with greedy algorithm improves the searching ability of the genetic algorithm.  ... 
doi:10.1109/iccsit.2010.5563867 fatcat:mofyvpsq25e3bk7am2bgdztoxy

A greedy genetic algorithm for the quadratic assignment problem

Ravindra K. Ahuja, James B. Orlin, Ashish Tiwari
2000 Computers & Operations Research  
The genetic algorithm incorporates many greedy principles in its design and, hence, we refer to it as a greedy genetic algorithm.  ...  The ideas we incorporate in the greedy genetic algorithm include (i) generating the initial population using a randomized construction heuristic; (ii) new crossover schemes; (iii) a special purpose immigration  ...  Acknowledgements We thank Bezalel Gavish for suggesting us to investigate genetic algorithms for QAP.  ... 
doi:10.1016/s0305-0548(99)00067-2 fatcat:yodorpvxa5cexdbgdgem5twtha

Solving Travelling Salesman Problem Using Greedy Genetic Algorithm GGA

Vinod Jain, Jay Shankar Prasad
2017 International Journal of Engineering and Technology  
Genetic Algorithm is used to solve these problems and the performance of genetic algorithm depends on its operators. In this paper new greedy genetic algorithm has been proposed to solve TSP.  ...  The proposed greedy genetic algorithm search deeper in the search space and find better solutions as compared to existing algorithms.  ...  In this paper greedy approach has been used in genetic algorithm.  ... 
doi:10.21817/ijet/2017/v9i2/170902188 fatcat:lhyk6vfbsjahfnjnb3cxhoz57q

Extracting Minimum Unsatisfiable Cores with a Greedy Genetic Algorithm [chapter]

Jianmin Zhang, Sikun Li, Shengyu Shen
2006 Lecture Notes in Computer Science  
In this paper, we propose an efficient greedy genetic algorithm to derive an exact or nearly exact minimum unsatisfiable core.  ...  The first two steps are the same as those of the greedy genetic algorithm; 2.  ...  We combine the greedy algorithm and the genetic algorithm to make up for the shortage of each other.  ... 
doi:10.1007/11941439_89 fatcat:ycwiq3fwwze7rlsm735qqomkqy

Genetic and Memetic Algorithm with Diversity Equilibrium based on Greedy Diversification [article]

Andrés Herrera-Poyatos, Francisco Herrera
2017 arXiv   pre-print
It confronts the diversity problem using the named greedy diversification operator.  ...  The lack of diversity in a genetic algorithm's population may lead to a bad performance of the genetic operators since there is not an equilibrium between exploration and exploitation.  ...  Genetic algorithm with diversity equilibrium based on greedy diversification.  ... 
arXiv:1702.03594v1 fatcat:ndfpmigrpvftrar5keyzwczrzq

Species Choice for Comparative Genomics: Being Greedy Works

Fabio Pardi, Nick Goldman
2005 PLoS Genetics  
Several projects investigating genetic function and evolution through sequencing and comparison of multiple genomes are now underway.  ...  Our mathematical formalization of this problem surprisingly shows that the best long-term cooperative strategy coincides with the seemingly shortterm "greedy" strategy of always choosing the next best  ...  FP derived the proof of correctness of the greedy algorithm.  ... 
doi:10.1371/journal.pgen.0010071 pmid:16327885 pmcid:PMC1298936 fatcat:zbne5dt2b5cxhcrz54hii7qreu

Species Choice for Comparative Genomics: Being Greedy Works

Fabio Pardi, Nick Goldman
2005 PLoS Genetics  
Several projects investigating genetic function and evolution through sequencing and comparison of multiple genomes are now underway.  ...  Our mathematical formalization of this problem surprisingly shows that the best long-term cooperative strategy coincides with the seemingly shortterm "greedy" strategy of always choosing the next best  ...  FP derived the proof of correctness of the greedy algorithm.  ... 
doi:10.1371/journal.pgen.0010071.eor fatcat:wopd4svoqfhhxp7w52xhw3okam

Data Source Selection Based on an Improved Greedy Genetic Algorithm

Jian Yang, Chunxiao Xing
2019 Symmetry  
We proposed an improved greedy genetic algorithm (IGGA) to solve the problem of source selection, and carried out a wide range of experimental evaluations on the real and synthetic dataset.  ...  • We propose an improved novel greedy genetic algorithm(IGGA).  ...  Table 6 . 6 Performance comparison of improved greedy genetic algorithm (IGGA), DGGA, BPSO and ACA.  ... 
doi:10.3390/sym11020273 fatcat:utkwrjcayfh6hk7g3fdjzta3t4

Applying greedy genetic algorithm on 0/1 multiple knapsack problem

Vinod Jain, Jay Shankar Prasad
2018 International Journal of Advanced Technology and Engineering Exploration  
In this paper MKP is solved using greedy genetic algorithm. The proposed genetic algorithm uses greedy approach in its selection and reproduction operations of GA.  ...  Keywords Multiple knapsack problem, Genetic algorithm, Greedy approach.  ...  algorithm Results for solving p01 MKP problem using the greedy genetic algorithmTable 4Results comparison using standard genetic algorithm and greedy genetic algorithm Multiple knapsack instance -p01  ... 
doi:10.19101/ijatee.2018.545018 fatcat:tzxnc46v5ja3lmkqtnmxsdwawe

Greedy-Genetic Algorithm Based Video Data Scheduling Over 5G Networks

E. Elamaran, B. Sudhakar
2022 Intelligent Automation and Soft Computing  
Initially, a Priority scheduling Technique based on the greedy and genetic algorithm is proposed for offering better QOS in reduced time durations.  ...  Genetic Algorithm is used for Optimizing the identified problems by means of relying on the selection attributes.  ...  Greedy Genetic Scheduling Genetic algorithms are able-bodied and ill-fitted to the analytic video frames-based scheduling problems as the clashing heuristic methods genetic algorithms accomplish on a citizenry  ... 
doi:10.32604/iasc.2022.020625 fatcat:j4ubqyh6ufa23atxqgbqgsjofa

A Greedy Genetic Algorithm for the TDMA Broadcast Scheduling Problem

Chih-Chiang LIN, Pi-Chung WANG
2013 IEICE transactions on information and systems  
We present three heuristic genetic operators, including a greedy crossover and two greedy mutation operators, to optimize both objectives of the BSP.  ...  In this work, we propose a greedy genetic algorithm for solving the BSP with a large number of nodes.  ...  In this paper, we propose a greedy genetic algorithm for the BSP. In our algorithm, we propose three greedy genetic operators, including a crossover and two mutation operators.  ... 
doi:10.1587/transinf.e96.d.102 fatcat:ammf2m6sercsxpiq67q2ekseja

A NOVEL GREEDY GENETIC ALGORITHM TO SOLVE COMBINATORIAL OPTIMIZATION PROBLEM

M. A. Basmassi, L. Benameur, J. A. Chentoufi
2020 The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences  
In this paper, a modified genetic algorithm based on greedy sequential algorithm is presented to solve combinatorial optimization problem.  ...  The algorithm proposed here is a hybrid of heuristic and computational intelligence algorithm where greedy sequential algorithm is used as operator inside genetic algorithm like crossover and mutation.  ...  THE PROPOSED APPROACH The proposed approach novel greedy genetic algorithm (NGGA) combines genetic algorithm (GA) and greedy sequential algorithm (GSA) to solve the GCP.  ... 
doi:10.5194/isprs-archives-xliv-4-w3-2020-117-2020 fatcat:3xycfwcenbajrctfgfr7faxhfi
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