Search Results - (( intelligence model scheduling algorithm ) OR ( intelligence based path algorithm ))
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African Buffalo Optimization (ABO): A New Metaheuristic Algorithm
Published 2015“…The African Buffalo Optimization (A.B.0) algorithm simulates the African buffalos' behaviour by encapsulation in a mathematical model; which solves a number of discrete optimization problems using graph-based route planning, job scheduling and it extends Swarm Intelligence paradigms. …”
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Multi agent quality of service routing based on scheme ant colony optimization algorithm
Published 2014“…The proposed scheme has been simulated by OMNET++ and compared with standard AntNet and two well-known standard QoS routings; Widest Shortest Path (WSP) algorithm and Shortest Widest Path (SWP) algorithm. …”
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Sustainability in intelligent building environments using weighted priority scheduling algorithm
Published 2017“…In this paper, we propose a new decision-making model with a weighted-priority scheduling algorithm that solves the conflicts to achieve efficient and sustainable communication response among heterogeneous systems. …”
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Mobile robot path planning using hybrid genetic algorithm and traversability vectors method
Published 2004“…Recent advances in robotics and machine intelligence have led to the application of modern optimization method such as the genetic algorithm (GA), to solve the path-planning problem. …”
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Intelligent Optimization Systems for MaintenanceScheduling of Power Plant Generators
Published 2024“…This paper presents a Genetic Algorithm (GA) and Ant-Colony (AC) optimization model for power plant generators� maintenance scheduling. …”
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Optimisation of Environmental Risk Assessment Architecture using Artificial Intelligence Techniques
Published 2024“…By contrast, the results of the safe path selection model were compared with the results obtained using Dijkstra's algorithm and the Floyd-Warshall algorithm. …”
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A Novel Path Prediction Strategy for Tracking Intelligent Travelers
Published 2009“…It is proposed and shown that route-like intelligent motion is based on a combination of decisional and kinematical factors. …”
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Hybrid ant colony system algorithm for static and dynamic job scheduling in grid computing
Published 2015“…One of the prominent intelligent algorithms is ant colony system (ACS) which is implemented widely to solve various types of scheduling problems. …”
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Performance Analysis of Swarm Intelligence-Based Routing Protocol for Mobile Ad Hoc Network and Wireless Mesh Networks
Published 2009“…Also the main aim of this research is to solve the freezing problem during optimum as well as sub-optimum path discovery process. In this research, Intelligent AntNet based Routing Algorithm (IANRA) is presented for routing in WMNs and MANET to find optimum and near-optimum paths for data packet routing. …”
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Time series data intelligent clustering algorithm for landslide displacement prediction
Published 2018“…To address this problem, an intelligent clustering algorithm for time series data in landslide displacement prediction based on nonlinear dynamic time bending is proposed in this paper. …”
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Optimization and control of hydro generation scheduling using hybrid firefly algorithm and particle swarm optimization techniques
Published 2018“…Secondly, this approach hybridizing the FA with the rough algorithm (RA), where RA is used to control the steps of randomness for the FA while optimizing the weights of the standard BPNN model. …”
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Adaptive route optimization for mobile robot navigation using evolutionary algorithm
Published 2021“…For example, Ant Colony Optimization (ACO) is an optimization algorithm based on swarm intelligence which is widely used to solve path planning problem. …”
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False path identification algorithm framework for nonseparable controller-data path circuits
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Modelling of heuristic distribution algorithm to optimize flexible production scheduling in Indian industry
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A hybrid sampling-based path planning algorithm for mobile robot navigation in unknown environments
Published 2013“…The motion planning problem poses the question of how a robot can move from an initial to a final position. Sampling-based motion planning is a class of randomized path planning algorithms with proven completeness. …”
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Managing risk in production scheduling under uncertain disruption
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