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Study on Query Optimization based Techniques using Stochastic Approaches

Daljinder Dugg, Mandeep Singh, Gurpreet Singh
2017 International Journal of Computer Applications  
The overall objective of this paper is to represent the various query optimization techniques using stochastic approaches which further optimize the design of query optimization genetic approaches.  ...  Query optimization is a stimulating task of any database system.  ...  Design of Simple Genetic Query Optimizer (SGQO) Simple Genetic Query Optimizer (SGQO) has been designed for solving the operation site allocation problem of distributed DSS queries.  ... 
doi:10.5120/ijca2017913482 fatcat:lhwgfelmibebjdtfzpdfcqb3tu

Design and analysis of stochastic DSS query optimizers in a distributed database system

Manik Sharma, Gurvinder Singh, Rajinder Singh
2016 Egyptian Informatics Journal  
The results of Entropy Based Restricted Stochastic Query Optimizer (ERSQO) are compared with the results of Exhaustive Enumeration Query Optimizer (EAQO), Simple Genetic Query Optimizer (SGQO), Novel Genetic  ...  Here, an innovative stochastic framework of DSS query optimizer is proposed to further optimize the design of existing query optimization genetic approaches.  ...  However, it can be effectively solved by stochastic approaches. Genetic Algorithm (GA) is a prevalent stochastic approach.  ... 
doi:10.1016/j.eij.2015.10.003 fatcat:k4avk6hfxvetnays44cnj7vc2y

Optimization of Cloud Database Route Scheduling Based on Combination of Genetic Algorithm and Ant Colony Algorithm

Zhang Yan-hua, Feng Lei, Yang Zhi
2011 Procedia Engineering  
For the cloud database route scheduling problem, this paper designed a cloud database route scheduling algorithm according to the dynamic combination of the genetic algorithm and ant colony algorithm.  ...  The initial solution got by the Genetic Algorithm was transformed into the pheromone initial value, which was needed by ant colony algorithm, then the optimal solution by the ant colony algorithm was obtained  ...  Dynamic Combination of Genetic Algorithm and Ant Colony Algorithm Genetic Algorithm Genetic algorithm, which comes from Genetics and Darwin industry, is a widely used searching method.  ... 
doi:10.1016/j.proeng.2011.08.626 fatcat:37xnewctqjek7gfrhj2mfaumqa

SQL Query Optimization Techniques

Priyanka R. Munot, Dipali R. Patil, Kajal P. Pathak
2019 IJARCCE  
To implement query optimization methods such as Heuristic Greedy based optimization, Iterative Improvement based cost optimization and Ant Colony optimization algorithms.  ...  Show Comparison of cost, execution time and response time between Heuristic Greedy based optimization; Ant Colony Optimization and Iterative Improvement based cost optimization algorithms  ...  Query optimization has been found very useful in increasing the database systems' performance in terms of time.  ... 
doi:10.17148/ijarcce.2019.8518 fatcat:ut3hnlsn4nd5dgooz3lmms74ki

Stochastic Analysis of DSS Queries for a Distributed Database Design

Manik Sharma, Gurvinder Singh, Rajinder Singh, Gurdev Singh
2013 International Journal of Computer Applications  
In this work an effort is made to find an optimal DSS sub query allocation plan in distributed environment stochastically using Genetic Algorithm.  ...  Optimization of query in distributed database system is one of the dominant subjects in the field of database theory.  ...  DSS queries are analyzed and optimized stochastically using Genetic Algorithm by considering Total Cost of System Resources as Fitness Function.  ... 
doi:10.5120/14447-2608 fatcat:nnwl6jjx4bgq7dl7sieayf6aeq

Research on a Heuristic GA-Based Decision Support System for Rice in Heilongjiang Province [chapter]

Ran Cao, Yushu Yang, Wei Guo
2011 IFIP Advances in Information and Communication Technology  
This study presents a heuristic genetic algorithm-based decision support system to search the optimal solution.  ...  GA has been regarded as an effective analytic tool and stochastic search technique to solve large and complicated problems.  ...  However, the oversimplified distribution of population will result in the lack of plurality and the genetic algorithm is prone to premature.  ... 
doi:10.1007/978-3-642-18336-2_39 fatcat:mxac7b52sjckfmc5oqcgm4w23m

A Novel Evolutionary Algorithm for Solving Static Data Allocation Problem in Distributed Database Systems

Ali Safari Mamaghani, Mostafa Mahi, Mohammad Reza Meybodi, Mohammad Hosseinzadeh Moghaddam
2010 2010 Second International Conference on Network Applications, Protocols and Services  
In this paper an approximate algorithm has been proposed. This algorithm is a hybrid evolutionary algorithm obtained from combining object migration learning automata and genetic algorithm.  ...  Given a distributed database system and a set of queries from each site, the objective of a data allocation algorithm is to locate the data fragments at different sites so as to minimize the total data  ...  A similar algorithm suggested by Corcoran was used for file allocation in distributed systems as well [10] . Another genetic-based algorithm was used by Ishfaq Ahmad et al. [1] .  ... 
doi:10.1109/netapps.2010.10 fatcat:yq3mku2nk5he7o63fgwe25gr5y

Design and comparative analysis of DSS queries in distributed environment

Manik Sharma, Gurvinder Singh, Rajinder Singh Virk, Gurdev Singh
2013 2013 International Computer Science and Engineering Conference (ICSEC)  
Programming, Genetic Algorithm and Entropy based Genetic Algorithm.The results of different query optimization approaches viz.  ...  Independent of the size and complexity of a DSS query, use of entropy with stochastic approach (HC-ERGA) provides an optimal solution in a very short and constant time.Furthermore, the results of HC-ERGA  ...  Exhaustive Enumeration, Dynamic Programming, Branch and Bound, Genetic Algorithm are used to solve the query optimization problem.  ... 
doi:10.1109/icsec.2013.6694756 fatcat:46ioskm5cvevljmnh3xtko6bwm

Comprehensive approach for solving multimodal data analysis problems based on integration of evolutionary, neural and deep neural network algorithms

I Ivanov, E Sopov, I Panfilov
2018 IOP Conference Series: Materials Science and Engineering  
learning algorithm that includes consecutive use of the genetic optimization algorithm and the back-propagation algorithm.  ...  In this work we propose the comprehensive approach for solving multimodal data analysis problems.  ...  Dataset and feature description SAVEE database was used for solving the emotion recognition problem in this work.  ... 
doi:10.1088/1757-899x/450/5/052007 fatcat:uaqlkkxwovfh3nfxa4w24dgy6i

Stochastic Heuristic Optimization based Multi-Query Processing in Wireless Sensor Network using Genetic Algorithm

S. AntonyAliceJeyaBharathi, K. Alagarsamy
2014 International Journal of Computer Applications  
To develop a multiple query processing strategy in wireless sensor network, Stochastic Heuristic Optimization using Genetic Algorithm (SHO-GA) is introduced.  ...  The multi-query processing using Genetic Algorithm (GA) takes the associations with FROM clause and other multiple query operators.  ...  The multi-query processing using genetic Algorithms contain the stochastic heuristic optimization methods which solves the multi-query processing with optimized result.  ... 
doi:10.5120/17002-7147 fatcat:vbceseynrncclbsii2g6q3zvqi

Coupling soft computing, simulation and optimization in supply chain applications: review and taxonomy

Hanane El Raoui, Mustapha Oudani, Ahmed El Hilali Alaoui
2020 IEEE Access  
In this paper we explore the near-full spectrum of optimization methods and simulation techniques.  ...  A review and taxonomy were performed to give an overview of the broad field of optimization/simulation approaches applied to solve supply chain problems.  ...  The model is solved using the weighting method, the genetic algorithm as well as the L-P metric method.  ... 
doi:10.1109/access.2020.2973329 fatcat:lqlghzdqafd4zksd7ziwrvdjou

A Pseudo-Parallel Genetic Algorithm Integrating Simulated Annealing for Stochastic Location-Inventory-Routing Problem with Consideration of Returns in E-Commerce

Bailing Liu, Hui Chen, Yanhui Li, Xiang Liu
2015 Discrete Dynamics in Nature and Society  
To solve the NP-hand problem, a pseudo-parallel genetic algorithm integrating simulated annealing (PPGASA) is proposed.  ...  We formulate a stochastic location-inventory-routing problem (LIRP) model with no quality defects returns.  ...  Although traditional genetic algorithm (GA) has strong global search ability in solving optimization problems, it has defects such as premature and weak local search ability.  ... 
doi:10.1155/2015/586581 fatcat:ncouo4ntzvg4rljjbes4g3jqby

Niche Pseudo-Parallel Genetic Algorithms for Path Optimization of Autonomous Mobile Robot - A Specific Application of TSP [chapter]

Zhihua Shen, Yingkai Zhao
2008 Traveling Salesman Problem  
As an optimal method applied with biologic genetics and evolutionary mechanism [5] , GA totally Open Access Database www.i-  ...  Genetic algorithm is numerical optimization method [4] based on the theory of genetics and natural selection.  ...  Parameters Used in NPPGA In the experiment, a single step NPPGA is used to solving the problem of path optimization and evolution of "Robot Tour". 8 optimal solutions can be obtained shown in table 2.  ... 
doi:10.5772/5585 fatcat:6fle4hpfgjdt3dsthnfgfflaey

A Bayesian Network Learning Algorithm Based on Independence Test and Ant Colony Optimization

Jun-Zhong JI, Hong-Xun ZHANG, Ren-Bing HU, Chun-Nian LIU
2009 Acta Automatica Sinica  
To solve the drawbacks of the ant colony optimization for learning Bayesian networks (ACO-B), this paper proposes an improved algorithm based on the conditional independence test and ant colony optimization  ...  The experimental results on the benchmark data sets show that the new algorithm is effective and efficient in large scale databases, and greatly enhances convergence speed compared to the original algorithm  ...  Learning Bayesian networks using ACO (ACO-B) Ant colony optimization (ACO), proposed by Dorigo in 1990 s [17−18] , is a new meta-heuristic search algorithm, which is often used to solve combinatorial  ... 
doi:10.1016/s1874-1029(08)60077-4 fatcat:xfdidmbr4rg7lloh6wcjrlnh3q

NMR Parameters Determination through ACE Committee Machine with Genetic Implanted Fuzzy Logic and Genetic Implanted Neural Network

Mojtaba Asoodeh, Parisa Bagheripour, Amin Gholami
2015 Acta Geophysica  
Firstly, artificial neural network (ANN) is optimized by virtue of hybrid genetic algorithm-pattern search (GA-PS) technique, then fuzzy logic (FL) is optimized by means of GA-PS, and eventually an alternative  ...  condition expectation (ACE) model is constructed using the concept of committee machine to combine outputs of optimized and non-optimized FL and ANN models.  ...  Hybrid genetic algorithm-pattern search technique Genetic algorithm is a stochastic global optimization tool which emulates the biological process of natural evolution for solving problems in widespread  ... 
doi:10.1515/acgeo-2015-0003 fatcat:lcl4odrdvnbtrnppyuvaklaeku
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