scholarly journals Sensor Location Problems As Test Problems Of Nonsmooth Optimization And Test Results Of A Few Nonsmooth Optimization Solvers

2012 ◽  
Vol 1 (2) ◽  
Author(s):  
Fuchun Huang
Keyword(s):  
Nonsmooth Optimization ◽  
Location Problems ◽  
Test Problems ◽  
Test Results ◽  
Sensor Location ◽  
Optimization Solvers

scholarly journals Comparative assessment of smooth and non-smooth optimization solvers in HANSO software

2021 ◽  
Vol 12 (1) ◽  
pp. 39-46
Author(s):  
Ali Hakan Tor
Keyword(s):  
Nonsmooth Optimization ◽  
Hybrid Algorithm ◽  
Optimization Problems ◽  
Optimization Methods ◽  
Comparative Assessment ◽  
Test Problems ◽  
Bfgs Method ◽  
Smooth Optimization ◽  
Optimization Solvers ◽  
Academic Test

The aim of this study is to compare the performance of smooth and nonsmooth optimization solvers from HANSO (Hybrid Algorithm for Nonsmooth Optimization) software. The smooth optimization solver is the implementation of the Broyden-Fletcher-Goldfarb-Shanno (BFGS) method and the nonsmooth optimization solver is the Hybrid Algorithm for Nonsmooth Optimization. More precisely, the nonsmooth optimization algorithm is the combination of the BFGS and the Gradient Sampling Algorithm (GSA). We use well-known collection of academic test problems for nonsmooth optimization containing both convex and nonconvex problems. The motivation for this research is the importance of the comparative assessment of smooth optimization methods for solving nonsmooth optimization problems. This assessment will demonstrate how successful is the BFGS method for solving nonsmooth optimization problems in comparison with the nonsmooth optimization solver from HANSO. Performance profiles using the number iterations, the number of function evaluations and the number of subgradient evaluations are used to compare solvers.

Anticipatory Dynamic Traffic Sensor Location Problems with Connected Vehicle Technologies

2018 ◽  
Vol 52 (6) ◽  
pp. 1299-1326 ◽  
Author(s):  
Hyoshin (John) Park ◽  
Ali Haghani ◽  
Song Gao ◽  
Michael A. Knodler ◽  
Siby Samuel
Keyword(s):  
Location Problems ◽  
Connected Vehicle ◽  
Sensor Location ◽  
Dynamic Traffic ◽  
Vehicle Technologies

Some Further Results for a Reduction Method in Nonhierarchical Optimization-Based Design

1992 ◽  
Author(s):  
Bi-Chu Wu ◽  
Shapour Azarm
Keyword(s):  
Optimality Conditions ◽  
Reduction Method ◽  
Numerical Test ◽  
Verification And Validation ◽  
Previous Article ◽  
Test Problems ◽  
Engineering Systems ◽  
Test Results ◽  
Simple Reduction ◽  
Optimization Based Design

Abstract In a previous article, a new and simple reduction method was presented for optimization-based design of nonhierarchically decomposed engineering systems. As a sequel to that work, in this paper we first examine some significant issues in relation to the reduction method: the optimality conditions when the method is applied, the reason why move limits are not required, and some of the factors that might affect the robustness of the cumulative constraints. For verification and validation, we then present some numerical test results in which the method is applied to twenty-one (21) test problems. Based on the test results reported, some guidelines for applying the method are suggested.

scholarly journals A Geometric Approach to Noisy EDM Resolution in FTM Measurements

Computers ◽  
2021 ◽  
Vol 10 (3) ◽  
pp. 33
Author(s):  
Jerome Henry ◽  
Nicolas Montavont ◽  
Yann Busnel ◽  
Romaric Ludinard ◽  
Ivan Hrasko
Keyword(s):  
Euclidean Distance ◽  
Geometric Approach ◽  
Least Square ◽  
Location Problems ◽  
Second Step ◽  
Floor Plan ◽  
Sensor Location ◽  
Indoor Location ◽  
Ranging Error ◽  
Asymmetrically Distributed

Metric Multidimensional Scaling is commonly used to solve multi-sensor location problems in 2D or 3D spaces. In this paper, we show that such technique provides poor results in the case of indoor location problems based on 802.11 Fine Timing Measurements, because the number of anchors is small and the ranging error asymmetrically distributed. We then propose a two-step iterative approach based on geometric resolution of angle inaccuracies. The first step reduces the effect of poor ranging exchanges. The second step reconstructs the anchor positions, starting from the distances of highest likely-accuracy. We show that this geometric approach provides better location accuracy results than other Euclidean Distance Metric techniques based on Least Square Error logic. We also show that the proposed technique, with the input of one or more known location, can allow a set of fixed sensors to auto-determine their position on a floor plan.

scholarly journals Heuristics for Mixed Strength Sensor Location Problems

2020 ◽  
Vol 11 (2) ◽  
pp. 53-65
Author(s):  
Rex K Kincaid ◽  
Robin M. Givens
Keyword(s):  
Environmental Conditions ◽  
Location Problems ◽  
Minimum Size ◽  
Geometric Graphs ◽  
Illegal Logging ◽  
Sensor Location ◽  
Rain Forests ◽  
Solution Quality ◽  
Location Detection ◽  
Location Sensor

Location-detection problems are pervasive. Examples include the detection of faults in microprocessors, the identification of contaminants in ventilation systems, and the detection of illegal logging in rain forests. In each of these applications a network provides a convenient modelling paradigm. Sensors are placed at particular node locations that, by design, uniquely detect and locate issues in the network. Open locating-dominating (OLD) sets constrain a sensor's effectiveness by assuming that it is unable to detect problems originating from the sensor location. Sensor failures may be caused by extreme environmental conditions or by the act of a nefarious individual. Determining the minimum size OLD set in a network is computationally intractable, but can be modelled as an integer linear program. The focus of this work is the development and evaluation of heuristics for the minimum OLD set problem when sensors of varying strengths are allowed. Computational experience and solution quality are reported for geometric graphs of up to 150 nodes.

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