scholarly journals Survey of 8 UAV Set-Covering Algorithms for Terrain Photogrammetry

2020 ◽  
Vol 12 (14) ◽  
pp. 2285 ◽  
Author(s):  
Joshua E. Hammond ◽  
Cory A. Vernon ◽  
Trent J. Okeson ◽  
Benjamin J. Barrett ◽  
Samuel Arce ◽  
...  
Keyword(s):  
Linear Programming ◽  
Pareto Front ◽  
Computational Cost ◽  
Set Covering ◽  
Greedy Heuristics ◽  
Order Of Magnitude ◽  
Covering Algorithms ◽  
Time Required ◽  
Grid Independence

Remote sensing with unmanned aerial vehicles (UAVs) facilitates photogrammetry for environmental and infrastructural monitoring. Models are created with less computational cost by reducing the number of photos required. Optimal camera locations for reducing the number of photos needed for structure-from-motion (SfM) are determined through eight mathematical set-covering algorithms as constrained by solve time. The algorithms examined are: traditional greedy, reverse greedy, carousel greedy (CG), linear programming, particle swarm optimization, simulated annealing, genetic, and ant colony optimization. Coverage and solve time are investigated for these algorithms. CG is the best method for choosing optimal camera locations as it balances number of photos required and time required to calculate camera positions as shown through an analysis similar to a Pareto Front. CG obtains a statistically significant 3.2 fewer cameras per modeled area than base greedy algorithm while requiring just one additional order of magnitude of solve time. For comparison, linear programming is capable of fewer cameras than base greedy but takes at least three orders of magnitude longer to solve. A grid independence study serves as a sensitivity analysis of the CG algorithms α (iteration number) and β (percentage to be recalculated) parameters that adjust traditional greedy heuristics, and a case study at the Rock Canyon collection dike in Provo, UT, USA, compares the results of all eight algorithms and the uniqueness (in terms of percentage comparisons based on location/angle metadata and qualitative visual comparison) of each selected set. Though this specific study uses SfM, the principles could apply to other instruments such as multi-spectral cameras or aerial LiDAR.

SOLVING LINEAR INTEGER PROGRAMMING PROBLEMS BY A NOVEL NEURAL MODEL

1999 ◽  
Vol 09 (01) ◽  
pp. 27-39 ◽  
Author(s):  
S. CAVALIERI
Keyword(s):  
Linear Programming ◽  
Integer Linear Programming ◽  
Travelling Salesman Problem ◽  
Neural Model ◽  
Hopfield Neural Network ◽  
Hopfield Model ◽  
Set Covering ◽  
Covering Problem ◽  
Linear Programming Problems ◽  
Time Required

The paper deals with integer linear programming problems. As is well known, these are extremely complex problems, even when the number of integer variables is quite low. Literature provides examples of various methods to solve such problems, some of which are of a heuristic nature. This paper proposes an alternative strategy based on the Hopfield neural network. The advantage of the strategy essentially lies in the fact that hardware implementation of the neural model allows for the time required to obtain a solution so as not depend on the size of the problem to be solved. The paper presents a particular class of integer linear programming problems, including well-known problems such as the Travelling Salesman Problem and the Set Covering Problem. After a brief description of this class of problems, it is demonstrated that the original Hopfield model is incapable of supplying valid solutions. This is attributed to the presence of constant bias currents in the dynamic of the neural model. A demonstration of this is given and then a novel neural model is presented which continues to be based on the same architecture as the Hopfield model, but introduces modifications thanks to which the integer linear programming problems presented can be solved. Some numerical examples and concluding remarks highlight the solving capacity of the novel neural model.

Developing Schedule With Linear Programming (Case Study: STTF II Project Komplek Sukamukti Banjaran)

2020 ◽  
Vol 4 (02) ◽  
pp. 34-45
Author(s):  
Naufal Dzikri Afifi ◽  
Ika Arum Puspita ◽  
Mohammad Deni Akbar
Keyword(s):  
Linear Programming ◽  
Objective Function ◽  
Project Scheduling ◽  
Time Limit ◽  
Minimum Time ◽  
Service Cost ◽  
Trade Off ◽  
Overtime Work ◽  
The Cost

Shift to The Front II Komplek Sukamukti Banjaran Project is one of the projects implemented by one of the companies engaged in telecommunications. In its implementation, each project including Shift to The Front II Komplek Sukamukti Banjaran has a time limit specified in the contract. Project scheduling is an important role in predicting both the cost and time in a project. Every project should be able to complete the project before or just in the time specified in the contract. Delay in a project can be anticipated by accelerating the duration of completion by using the crashing method with the application of linear programming. Linear programming will help iteration in the calculation of crashing because if linear programming not used, iteration will be repeated. The objective function in this scheduling is to minimize the cost. This study aims to find a trade-off between the costs and the minimum time expected to complete this project. The acceleration of the duration of this study was carried out using the addition of 4 hours of overtime work, 3 hours of overtime work, 2 hours of overtime work, and 1 hour of overtime work. The normal time for this project is 35 days with a service fee of Rp. 52,335,690. From the results of the crashing analysis, the alternative chosen is to add 1 hour of overtime to 34 days with a total service cost of Rp. 52,375,492. This acceleration will affect the entire project because there are 33 different locations worked on Shift to The Front II and if all these locations can be accelerated then the duration of completion of the entire project will be effective

scholarly journals Evaluating Life Cycle of Buildings Using an Integrated Approach Based on Quantitative-Qualitative and Simplified Best-Worst Methods (QQM-SBWM)

2021 ◽  
Vol 13 (8) ◽  
pp. 4487
Author(s):  
Maghsoud Amiri ◽  
Mohammad Hashemi-Tabatabaei ◽  
Mohammad Ghahremanloo ◽  
Mehdi Keshavarz-Ghorabaee ◽  
Edmundas Kazimieras Zavadskas ◽  
...  
Keyword(s):  
Life Cycle ◽  
Computer Software ◽  
Integrated Approach ◽  
Comfort Level ◽  
Combination Method ◽  
New Combination ◽  
Numerical Examples ◽  
Environmental Consequences ◽  
Time Required

Evaluating the life cycle of buildings is a valuable tool for assessing sustainability and analyzing environmental consequences throughout the construction operations of buildings. In this study, in order to determine the importance of building life cycle evaluation indicators, a new combination method was used based on a quantitative-qualitative method (QQM) and a simplified best-worst method (SBWM). The SBWM method was used because it simplifies BWM calculations and does not require solving complex mathematical models. Reducing the time required to perform calculations and eliminating the need for complicated computer software are among the advantages of the proposed method. The QQM method has also been used due to its ability to evaluate quantitative and qualitative criteria simultaneously. The feasibility and applicability of the SBWM were examined using three numerical examples and a case study, and the results were evaluated. The results of the case study showed that the criteria of the estimated cost, comfort level, and basic floor area were, in order, the most important criteria among the others. The results of the numerical examples and the case study showed that the proposed method had a lower total deviation (TD) compared to the basic BWM. Sensitivity analysis results also confirmed that the proposed approach has a high degree of robustness for ranking and weighting criteria.

scholarly journals Statistical Uncertainty of DNS in Geometries without Homogeneous Directions

2021 ◽  
Vol 11 (4) ◽  
pp. 1399
Author(s):  
Jure Oder ◽  
Cédric Flageul ◽  
Iztok Tiselj
Keyword(s):  
Channel Flow ◽  
A Priori ◽  
Time Integration ◽  
Navier Stokes ◽  
Statistical Uncertainty ◽  
Time Step ◽  
Order Of Magnitude ◽  
Averaging Time ◽  
The Individual ◽  
Time Required

In this paper, we present uncertainties of statistical quantities of direct numerical simulations (DNS) with small numerical errors. The uncertainties are analysed for channel flow and a flow separation case in a confined backward facing step (BFS) geometry. The infinite channel flow case has two homogeneous directions and this is usually exploited to speed-up the convergence of the results. As we show, such a procedure reduces statistical uncertainties of the results by up to an order of magnitude. This effect is strongest in the near wall regions. In the case of flow over a confined BFS, there are no such directions and thus very long integration times are required. The individual statistical quantities converge with the square root of time integration so, in order to improve the uncertainty by a factor of two, the simulation has to be prolonged by a factor of four. We provide an estimator that can be used to evaluate a priori the DNS relative statistical uncertainties from results obtained with a Reynolds Averaged Navier Stokes simulation. In the DNS, the estimator can be used to predict the averaging time and with it the simulation time required to achieve a certain relative statistical uncertainty of results. For accurate evaluation of averages and their uncertainties, it is not required to use every time step of the DNS. We observe that statistical uncertainty of the results is uninfluenced by reducing the number of samples to the point where the period between two consecutive samples measured in Courant–Friedrichss–Levy (CFL) condition units is below one. Nevertheless, crossing this limit, the estimates of uncertainties start to exhibit significant growth.

scholarly journals A Model for Developing Existing Ports Considering Economic Impact and Network Connectivity

2021 ◽  
Vol 13 (7) ◽  
pp. 3705
Author(s):  
Veterina Nosadila Riaventin ◽  
Sofyan Dwi Cahyo ◽  
Ivan Kristianto Singgih
Keyword(s):  
Network Connectivity ◽  
Economic Consequences ◽  
Real Problem ◽  
Container Transportation ◽  
Container Ports ◽  
Investment Priority ◽  
Time Required ◽  
Transportation Flows ◽  
Port Clusters

This study discusses the problem of determining which container port should be developed within an existing network and when this should be carried out. A case study of Indonesia’s port network is presented, where several new ports are to be improved to ensure smooth interisland transportation flows of goods. The effects of the investment on economic consequences and increased network connectivity are assessed. When improving the ports, we consider that the available budget limits the investment. The network connectivity is evaluated by considering the number of reachable ports from the developed ports or transportation time required from other ports within the same port cluster. Based on our knowledge, our study is the first one that discusses the investment problem in multiple container ports under single management, as well as its effects regarding the increase in container flows. The problem is introduced and three mathematical models are proposed and used to solve a real problem. The results show that different models have different improved aspects of container transportation flows—e.g., a balanced improvement of the whole port network (Model 2) and appropriate investment priority for port clusters (Model 3).

Pros and cons of time-dependent hybrid density functional approach to optical spectra of solids: a case study of CeO2

2021 ◽  
Author(s):  
Huai-Yang Sun ◽  
Shuo-Xue Li ◽  
Hong Jiang
Keyword(s):  
First Principles ◽  
Density Functional ◽  
Computational Cost ◽  
Optical Spectra ◽  
First Principles Calculation ◽  
Many Body ◽  
Many Body Perturbation Theory ◽  
Pros And Cons ◽  
Hybrid Density Functional

Prediction of optical spectra of complex solids remains a great challenge for first-principles calculation due to the huge computational cost of the state-of-the-art many-body perturbation theory based GW-Bethe Salpeter equation...

Rapid Polymer/Gas Solution Formation for Continuous Production of Microcellular Plastics

1996 ◽  
Vol 118 (4) ◽  
pp. 639-645 ◽  
Author(s):  
C. B. Park ◽  
N. P. Suh
Keyword(s):  
Rapid Heating ◽  
Continuous Production ◽  
Batch Process ◽  
Bubble Nucleation ◽  
Cycle Times ◽  
Solution Formation ◽  
Microcellular Plastics ◽  
Diffusion Phenomena ◽  
Order Of Magnitude ◽  
Time Required

An extrusion system that can create a polymer/gas solution rapidly for continuous processing of microcellular plastics is presented. Microcellular plastics are characterized by cell densities greater than 109 cells/cm3 and fully grown cells smaller than 10 μm. Previously these microcellular structures have been produced in a batch process by saturating a polymeric material with an inert gas under high pressure followed by inducing a rapid drop in the gas solubility. The diffusion phenomena encountered in this batch processing is typically slow, resulting in long cycle times. In order to produce microcellular plastics at industrial production rates, a means for the rapid solution formation is developed. The processing time required for completing the solution formation in the system was estimated from experimental data and the dispersive mixing theory based on an order-of-magnitude analysis. A means for promoting high bubble nucleation rates in the gas-saturated polymer via rapid heating is also discussed. The feasibility of the continuous production of microcellular plastics by the rapid polymer/gas solution formation and rapid heating was demonstrated through experiments. The paper includes not only a brief treatment of the basic science of the polymer/gas systems, but also the development of an industrially viable technology that fully utilizes the unique properties of microcellular plastics.

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