4,473 Hits in 4.3 sec

Editorial to special issue on evolutionary computation in dynamic and uncertain environments

Shengxiang Yang, Yew-Soon Ong, Yaochu Jin
2006 Genetic Programming and Evolvable Machines  
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

Yew-Soon Ong, Natalio Krasnogor, Hisao Ishibuchi
2007 IEEE Transactions on Systems Man and Cybernetics Part B (Cybernetics)  
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]

Zeng Bin, Luo Zhaohui, Wei Jun
2007 Lecture Notes in Computer Science  
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]

Uwe Aickelin, Adrian Adewunmi
2008 arXiv   pre-print
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

Priyanka Rani, Shakti Nagpal
2014 IOSR Journal of Computer Engineering  
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

Golnar Gharooni-fard, Fahime Moein-darbari, Hossein Deldari, Anahita Morvaridi
2010 Procedia Computer Science  
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

Karamath Ateeq, Manas Ranjan Pradhan, Beenu Mago
2020 Advances in Science, Technology and Engineering Systems  
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

Supreeth S, Kirankumari Patil
2022 International Journal of Emerging Technologies in Learning (iJET)  
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

Yanhong Wang, Dandan Ji
2015 International Journal of Computer and Communication Engineering  
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

Michele Amoretti
2010 Procedia Computer Science  
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  
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

M. Gerdes
2013 Expert systems with applications  
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

Junichi Suzuki, Pruet Boonma
2014 Proceedings of the 2014 conference companion on Genetic and evolutionary computation companion - GECCO Comp '14  
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

Sebastián García-Galán, Rocío Pérez de Prado, Jose Enrique Munoz Expósito
2013 Image Processing & Communications  
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

Mudra S Gondane
2012 IOSR Journal of Mechanical and Civil Engineering  
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
« Previous Showing results 1 — 15 out of 4,473 results