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Editorial to special issue on evolutionary computation in dynamic and uncertain environments
2006
Genetic Programming and Evolvable Machines
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in dynamic environments, or to find a robust solution that operates optimally in the presence of uncertainties. ...
., hardware design and job shop scheduling, are subjected to dynamic and uncertain environments that are often impossible to avoid in practice. ...
Yao Wang and Mark Wineberg contribute the third interesting paper, focusing on genetic algorithms (GAs) in dynamic environments. ...
doi:10.1007/s10710-006-9016-4
fatcat:wgmt3m37ivawxom3qspx3sguee
Special Issue on Memetic Algorithms
2007
IEEE Transactions on Systems Man and Cybernetics Part B (Cybernetics)
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He is Guest Editor of Genetic Programming and Evolvable Machines Journal dedicated to Evolutionary Computation in Dynamic and Uncertain Environments. ...
The approach reports success even in the presence of noisy objective functions. ...
doi:10.1109/tsmcb.2006.883274
fatcat:7gdkkxbourap5a33ayv2pmfmmq
Grid Scheduling Optimization Under Conditions of Uncertainty
[chapter]
2007
Lecture Notes in Computer Science
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In this paper we address the problem of delivering a deadline based scheduling in a dynamic and uncertain environment represented by dynamic Bayesian network based stochastic resource model. ...
The genetic algorithm is used to find the optimal and robust solutions so that the highest probability of satisfying the user's QoS objectives at a specified deadline can be achieved. ...
In iterations of the genetic algorithm, since we choose candidate scheduling strategies, . ...
doi:10.1007/978-3-540-74784-0_6
fatcat:ctnlrcm3lrdzpa5kkucu4kazmy
Simulation Optimization of the Crossdock Door Assignment Problem
[article]
2008
arXiv
pre-print
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The main advantage of using Memetic algorithms is that it combines a local search with Genetic Algorithms. ...
The novel aspect of our solution approach is that we intend to use simulation to derive a more realistic objective function and use Memetic algorithms to find an optimal solution. ...
handle noisy objective functions; we are interested in comparing the performance of Memetic algorithms to other popular heuristics in relation to noisy objective functions [4]. ...
arXiv:0803.1576v1
fatcat:o7odzvohara7rjryuyuubbgk5m
Dynamic Process Scheduling and Sequencing Using Genetic Algorithm
2014
IOSR Journal of Computer Engineering
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The scheduling is considered as NP hard problem .In this paper, we use the power of genetic algorithm to provide the efficient process scheduling. ...
This paper present the implementation of genetic algorithm for operating system process scheduling. ...
This paper is based on implementing a scheduling based Genetic algorithm concepts and making a comparison of it with SJF and FCFS scheduling algorithms based on the average waiting time of these algorithms ...
doi:10.9790/0661-16394853
fatcat:w2j2zaczcfdl7cwh5sltl656cu
Scheduling of scientific workflows using a chaos-genetic algorithm
2010
Procedia Computer Science
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Since, many applications are described in the form of dependent tasks, scheduling of these workflows has become a major challenge in grid environment. ...
In this paper, a novel genetic algorithm called chaos-genetic algorithm is used to solve the scheduling problem considering both user's budget and deadline. ...
In this paper a Chaos-Genetic Scheduling alg genetic algorithms when looking for an optimal variable [11] . ...
doi:10.1016/j.procs.2010.04.160
fatcat:wtly4u354jfjlg76y2az4wjw5u
Elasticity Based Med-Cloud Recommendation System for Diabetic Prediction in Cloud Computing Environment
2020
Advances in Science, Technology and Engineering Systems
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The Adaptively Toggle Genetic Algorithm (ATGA) is applied for elastic resource allocation while increase in the number of data sets. ...
In order to improve the existing algorithm performance, the computing and storage resources are insufficient in traditional data mining environment. ...
K means algorithm was used in [17] to remove noisy data and Genetic Algorithm was applied to find the optimal set of features. ...
doi:10.25046/aj0506193
fatcat:ewsuorzbb5cspled3y3fswiyv4
Hybrid Genetic Algorithm and Modified-Particle Swarm Optimization Algorithm (GA-MPSO) for Predicting Scheduling Virtual Machines in Educational Cloud Platforms
2022
International Journal of Emerging Technologies in Learning (iJET)
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So to enhance the energy efficiency and to provide the resources in an optimized way, a VM Scheduling mechanism with Hybrid Genetic Algorithm-Modified Particle Swarm Optimization (GA-MPSO) is proposed ...
The proposed approach, when compared to other VM scheduling algorithms, it intensifies the energy consumption to 105KWH, SLA violation rate of 0.08%, reduces the migrations count to 2122, and consumes ...
Algorithm 1 shows the Genetic Algorithm. An individual is defined by a set of parameters (variables) known as Genes in a genetic algorithm. ...
doi:10.3991/ijet.v17i07.29223
fatcat:bz23vumxuzbgdnvxefdv5ota3m
Data- and Rule-Based Integrated Mechanism for Job Shop Scheduling
2015
International Journal of Computer and Communication Engineering
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In this paper, a new data-based mechanism has been proposed to solve job shop scheduling problems (JSPs). ...
The simulation result of a simplified scheduling problem is presented as a preliminary validation to show the feasibility of the proposed integrated scheduling mechanism. ...
Recently, data-based scheduling has emerged as a new way to solving JSPs in such a manufacturing environment supporting by on-and off-line data accumulated and stored in data base. ...
doi:10.17706/ijcce.2015.4.3.180-186
fatcat:ox3vksi5cfeghc7mwqbwy35mpi
Towards fully autonomic peer-to-peer systems
2010
Procedia Computer Science
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in response to the environment, and turns the P2P network in a complex adaptive system (CAS). ...
Large-scale distributed applications are becoming more and more demanding in terms of efficiency and flexibility of the technological infrastructure, for which traditional solutions based on the client ...
Each environmental input usually targets a subset of the whole set of peers in the network. ...
doi:10.1016/j.procs.2010.04.297
fatcat:4yacpqjttvc5tdf2jy6rrapvju
Page 7258 of Mathematical Reviews Vol. , Issue 2004i
[page]
2004
Mathematical Reviews
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Gadeo Mar- tos and Luis Magdalena, Study of fuzzy logic controllers (FLCs), temporal fuzzy logic controllers (TFLCs) and faded temporal fuzzy logic controllers (FTFLCs) in noisy environments (127
39
R. ...
A.
68 COMPUTER SCIENCE 7258
Jiménez, P. D. Cuesta and G. Winter, A dynamical model of the simple genetic algorithm (343-347). ...
Decision trees and genetic algorithms for condition monitoring forecasting of aircraft air conditioning
2013
Expert systems with applications
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This paper proposes a method for forecasting the condition of aircraftt air conditioning system based on observed past data. Forecasting is done in a point by point way, by iterating the algorithm. ...
A genetic algorithm is used to find the best feature set for the given problem to increase the forecasting performance. ...
A sample decision tree can be seen in
Genetic Algorithms Genetic algorithms belong to the class of heuristic local search algorithms. ...
doi:10.1016/j.eswa.2013.03.025
fatcat:kxkzmbdfsrgbbg3gsffnkpxdbe
Noise-aware evolutionary TDMA optimization for neuronal signaling in medical sensor-actuator networks
2014
Proceedings of the 2014 conference companion on Genetic and evolutionary computation companion - GECCO Comp '14
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Simulation results show that the proposed optimizer efficiently obtains quality TDMA signaling schedules and operates a TDMA protocol by balancing conflicting objectives in noisy environments. ...
evolutionary algorithm. ...
This paper extends [26] by considering communication robustness as well as communication performance in noisy environments. ...
doi:10.1145/2598394.2609854
dblp:conf/gecco/SuzukiB14
fatcat:buea5yixsrapjc6pz7g77j7bse
Uncertainty-tolerant scheduling strategies for grid computing: knowledge-based techniques with bio-inspired learning
2013
Image Processing & Communications
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In this paper, a review of scheduling strategies dealing with uncertainty in systems information by the application of techniques such as fuzzy logic, neural networks or evolutionary algorithms is presented ...
Nevertheless, a major issue in the sharing of resources is the scheduling problem in a high-dynamic and uncertain environment where resources may become available, inactive or reserved over time according ...
In this paper, a review of scheduling strategies dealing with uncertainty in systems information by the application of techniques such as fuzzy logic, neural networks or evolutionary algorithms is presented ...
doi:10.2478/v10248-012-0073-4
fatcat:yrbkkwaewjexxdoxd2ffrqvhsa
Staff Scheduling in Health Care Systems
2012
IOSR Journal of Mechanical and Civil Engineering
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This paper deals with Genetic Algorithm (GA) approach to solve a specific Staff Scheduling Problem. ...
Staff scheduling is found as a crucial part of staff management. ...
A number of researchers have used genetic algorithms to solve the staff-scheduling problem. ...
doi:10.9790/1684-0162840
fatcat:aiwcjuj3jngsjktno2vrhve2wu
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