scholarly journals On a generalization of Nemhauser and Trotter's local optimization theorem

2017 ◽  
Vol 84 ◽  
pp. 97-106 ◽  
Author(s):  
Mingyu Xiao
Keyword(s):  
Local Optimization ◽  
Optimization Theorem

scholarly journals A generalization of Nemhauser and Trotterʼs local optimization theorem

2011 ◽  
Vol 77 (6) ◽  
pp. 1141-1158 ◽  
Author(s):  
Michael R. Fellows ◽  
Jiong Guo ◽  
Hannes Moser ◽  
Rolf Niedermeier
Keyword(s):  
Local Optimization ◽  
Optimization Theorem

scholarly journals Path planning for mobile robot using an enhanced ant colony optimization and path geometric optimization

2021 ◽  
Vol 18 (3) ◽  
pp. 172988142110192
Author(s):  
Songcan Zhang ◽  
Jiexin Pu ◽  
Yanna Si ◽  
Lifan Sun
Keyword(s):  
Path Planning ◽  
Convergence Rate ◽  
Mobile Robot ◽  
Local Optimization ◽  
Ant Colony ◽  
Ant Colony System ◽  
Geometric Features ◽  
Robot Path Planning ◽  
Computation Efficiency ◽  
Robot Path

Path planning of mobile robots in complex environments is the most challenging research. A hybrid approach combining the enhanced ant colony system with the local optimization algorithm based on path geometric features, called EACSPGO, has been presented in this study for mobile robot path planning. Firstly, the simplified model of pheromone diffusion, the pheromone initialization strategy of unequal allocation, and the adaptive pheromone update mechanism have been simultaneously introduced to enhance the classical ant colony algorithm, thus providing a significant improvement in the computation efficiency and the quality of the solutions. A local optimization method based on path geometric features has been designed to further optimize the initial path and achieve a good convergence rate. Finally, the performance and advantages of the proposed approach have been verified by a series of tests in the mobile robot path planning. The simulation results demonstrate that the presented EACSPGO approach provides better solutions, adaptability, stability, and faster convergence rate compared to the other tested optimization algorithms.

scholarly journals Design and Automated Optimization of an Internal Turret Mooring System in the Frequency and Time Domain

2021 ◽  
Vol 9 (6) ◽  
pp. 581
Author(s):  
Hongrae Park ◽  
Sungjun Jung
Keyword(s):  
System Design ◽  
Time Domain ◽  
Initial Conditions ◽  
Minimum Weight ◽  
Optimization Algorithms ◽  
Local Optimization ◽  
Mooring System ◽  
Floating Offshore Wind Turbines ◽  
Global And Local Optimization ◽  
Global And Local

A cost-effective mooring system design has been emphasized for traditional offshore industry applications and in the design of floating offshore wind turbines. The industry consensus regarding mooring system design is mainly inhibited by previous project experience. The design of the mooring system also requires a significant number of design cycles. To take aim at these challenges, this paper studies the application of an optimization algorithm to the Floating Production Storage and Offloading (FPSO) mooring system design with an internal turret system at deep-water locations. The goal is to minimize mooring system costs by satisfying constraints, and an objective function is defined as the minimum weight of the mooring system. Anchor loads, a floating body offset and mooring line tensions are defined as constraints. In the process of optimization, the mooring system is analyzed in terms of the frequency domain and time domain, and global and local optimization algorithms are also deployed towards reaching the optimum solution. Three cases are studied with the same initial conditions. The global and local optimization algorithms successfully find a feasible mooring system by reducing the mooring system cost by up to 52%.

Genetic algorithm with local optimization

1995 ◽  
Vol 73 (4) ◽  
pp. 335-341 ◽  
Author(s):  
Károly F. Pál
Keyword(s):  
Genetic Algorithm ◽  
Local Optimization
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