scholarly journals Time-Aware and Temperature-Aware Fire Evacuation Path Algorithm in IoT-Enabled Multi-Story Multi-Exit Buildings

Sensors ◽  
2020 ◽  
Vol 21 (1) ◽  
pp. 111
Author(s):  
Hong-Hsu Yen ◽  
Cheng-Han Lin ◽  
Hung-Wei Tsao
Keyword(s):  
Open Space ◽  
Extreme Case ◽  
Temperature Limit ◽  
Shopping Mall ◽  
Computational Time ◽  
Computational Results ◽  
Fire Evacuation ◽  
Total Temperature ◽  
Taipei 101 ◽  
Time Aware

Temperature sensors with a communication capability can help monitor and report temperature values to a control station, which enables dynamic and real-time evacuation paths in fire emergencies. As compared to traditional approaches that identify a one-shot fire evacuation path, in this paper, we develop an intelligent algorithm that can identify time-aware and temperature-aware fire evacuation paths by considering temperature changes at different time slots in multi-story and multi-exit buildings. We first propose a method that can map three-dimensional multi-story multi-exit buildings into a two-dimensional graph. Then, a mathematical optimization model is proposed to capture this time-aware and temperature-aware evacuation path problem in multi-story multi-exit buildings. Six fire evacuation algorithms (BFS, SP, DBFS, TABFS, TASP and TADBFS) are proposed to identify the efficient evacuation path. The first three algorithms that do not address human temperature limit constraints can be used by rescue robots or firemen with fire-proof suits. The last three algorithms that address human temperature limit constraints can be used by evacuees in terms of total time slots and total temperature on the evacuation path. In the computational experiments, the open space building and the Taipei 101 Shopping Mall are all tested to verify the solution quality of these six algorithms. From the computational results, TABFS, TASP and TADBF identify almost the same evacuation path in open space building and the Taipei 101 Shopping Mall. BFS, SP DBFS can locate marginally better results in terms of evacuation time and total temperature on the evacuation path. When considering evacuating a group of evacuees, the computational time of the evacuation algorithm is very important in a time-limited evacuation process. Considering the extreme case of seven fires in eight emergency exits in the Taipei 101 Shopping Mall, the golden window for evacuation is 15 time slots. Only TABFS and TADBFS are applicable to evacuate 1200 people in the Taipei 101 Shopping Mall when one time slot is setting as one minute. The computational results show that the capacity limit for the Taipei 101 Shopping Mall is 800 people in the extreme case of seven fires. In this case, when the number of people in the building is less than 700, TADBFS should be adopted. When the number of people in the building is greater than 700, TABFS can evacuate more people than TADBFS. Besides identifying an efficient evacuation path, another significant contribution of this paper is to identify the best sensor density deployment at large buildings like the Taipei 101 Shopping Mall in considering the fire evacuation.

The Application of Fuzzification for Solving Quadratic Functions

2021 ◽  
Author(s):  
Lunshan Gao
Keyword(s):  
Approximate Solution ◽  
Approximation Algorithm ◽  
Critical Point ◽  
Numerical Experiments ◽  
Optimization Problems ◽  
Local Minimizer ◽  
Quadratic Functions ◽  
Computational Time ◽  
Computational Results ◽  
Average Computational Time

Abstract This paper describes an approximation algorithm for solving standard quadratic optimization problems(StQPs) over the standard simplex by using fuzzification technique. We show that the approximate solution of the algorithm is an epsilon -critical point and satisfies epsilon-delta condition. The algorithm is compared with IBM ILOG CPLEX (short for CPLEX). The computational results indicate that the new algorithm is faster than CPLEX. Especially for infeasible problems. Furthermore, we calculate 100 instances for different size StQP problems. The numerical experiments show that the average computational time of the new algorithm for calculating the first local minimizer is in BigO(n) when the size of the problems is less or equal to 450.

Turbine Performance Under Pulsating Inflow: A Similarity Analysis

2016 ◽  
Author(s):  
Hua Chen ◽  
Apostolos Pesiridis
Keyword(s):  
Strouhal Number ◽  
Similarity Analysis ◽  
Relative Importance ◽  
Computational Results ◽  
Gasoline Engines ◽  
Turbine Performance ◽  
Dimensional Parameters ◽  
Total Temperature ◽  
Inflow Conditions ◽  
Unsteady Conditions

Turbocharger turbines for diesel and gasoline engines work under pulsating inflow conditions. This paper discusses the influences of such unsteady conditions on turbine performance through a similarity analysis. First the assumptions for the analysis are described and key non-dimensional parameters are identified. Some of these parameters are further studied with the assistance from experimental and computational results in the open literature. Strouhal number, which expresses the relative importance of unsteady influences, is discussed in details regarding its definition, its application to experimental setup, and how it affects different components of the turbines. The analysis shows that Strouhal number should be scaled with the square root of turbine inlet total temperature.

Multi Robot Exploration through Pruning Frontiers

2012 ◽  
Vol 462 ◽  
pp. 609-616 ◽  
Author(s):  
Anshika Pal ◽  
Ritu Tiwari ◽  
Anupam Shukla
Keyword(s):  
Open Space ◽  
Clustering Algorithm ◽  
Unsupervised Clustering ◽  
Search And Rescue ◽  
Computational Time ◽  
Navigation Strategy ◽  
Key Issues ◽  
The Individual ◽  
Target Locations ◽  
Multi Robot

In this paper, an approach to multi robot exploration is presented. One of the key issues in multi robot exploration is how to assign target locations to the individual robots and how to better distribute the robots over the environment. The proposed technique applies a well-known unsupervised clustering algorithm (k-means) in order to fairly divide the space into as many disjoint regions as available robots. Hungarian Method is used for the assignment of robots to the individual regions with the task to explore the corresponding area. To drive the robots around the environment, a frontier ‘regions on the boundary between open space and unexplored space’ based navigation strategy is used to decide where to move next, according to the data collected so far. Furthermore, we discuss improvements to the frontier based exploration strategy, by pruning the frontier cells that further reduces the computational time. The numbers of candidate locations are evaluated based on three criteria: number of unknown cells, number of known cells and real path travelling cost. Simulations are presented to show the performance of the proposed technique. This method can best be applied in search and rescue operations, partitioning helps to explore different regions of the workspace parallely by different robots instead of concentrating efforts in particular spot, pruning helps to make movement decisions much faster, the result is that the potential victims in a region will not have to wait much longer.

A HYBRID GREEDY RANDOMIZED ADAPTIVE SEARCH HEURISTIC TO SOLVE THE DIAL-A-RIDE PROBLEM

2013 ◽  
Vol 30 (01) ◽  
pp. 1250046 ◽  
Author(s):  
FRANCESCA GUERRIERO ◽  
MARIA ELENA BRUNI ◽  
FRANCESCA GRECO
Keyword(s):  
Hybrid Approach ◽  
Terms Of Trade ◽  
Computational Time ◽  
Test Problems ◽  
Fixed Costs ◽  
Computational Results ◽  
Adaptive Search ◽  
Solution Quality ◽  
Search Heuristic ◽  
Number Of Customers

This paper presents a hybrid metaheuristic for solving the static dial-a-ride problem with heterogeneous vehicles and fixed costs. The hybridization combines a reactive greedy randomized adaptive search, used as outer scheme, with a tabu search heuristic in the local search phase. The algorithm is evaluated on well-known instances taken from the literature and on a set of randomly generated test problems, varying in the number of customers. Extensive computational results show the effectiveness of the hybrid approach in terms of trade-off between solution quality and computational time.

Iterative magnetic forward modeling for high susceptibility based on integral equation and Gauss-fast Fourier transform

Geophysics ◽  
2019 ◽  
Vol 85 (1) ◽  
pp. J1-J13 ◽  
Author(s):  
Fang Ouyang ◽  
Longwei Chen
Keyword(s):  
Integral Equation ◽  
Fourier Transform ◽  
Fast Fourier Transform ◽  
Extreme Case ◽  
Computational Time ◽  
Acceptable Result ◽  
Iterative Computation ◽  
Wide Range ◽  
Numerical Precision ◽  
Complex Target

Self-demagnetization due to strongly magnetic bodies can seriously affect the interpretation of magnetic anomalies. Conventional numerical methods often neglect the self-demagnetization effects and limit their use to low susceptibilities ([Formula: see text]). We have developed a novel iterative method based on the integral equation and the Gauss-fast Fourier transform (FFT) technique for calculating the magnetic field from finite bodies of high magnetic susceptibility and arbitrary shapes. The method uses a segmented model consisting of prismatic voxels to approximate a complex target region. In each voxel, the magnetization is assumed to be constant, so that the integral equation in the spatial domain can reduce to a simple form with lots of merit in numerical calculation after the 2D Fourier transform. Moreover, a contraction operator is derived to ensure the convergence of the iterative calculation, and the Gauss-FFT technique is applied to reduce numerical errors due to edge effects. Our modeling results indicate that this new iterative scheme performs well in a wide range of magnetic susceptibilities (1–1000 SI). For lower susceptibilities ([Formula: see text]), the iterative algorithm converges rapidly and indicates very good correlation with the analytical solutions. At higher susceptibilities ([Formula: see text]), our method still performs well, but the numerical accuracy improves with a relatively slow speed. In the extreme case ([Formula: see text]), an acceptable result is also obtained after sufficient iterative computation. A further improvement in the numerical precision can be achieved by increasing the number of prismatic voxels, but at the same time, the computational time increases linearly with the size of the voxels.

SOLVING THE UNCAPACITATED MULTIPLE ALLOCATION p-HUB CENTER PROBLEM BY GENETIC ALGORITHM

2006 ◽  
Vol 23 (04) ◽  
pp. 425-437 ◽  
Author(s):  
JOZEF KRATICA ◽  
ZORICA STANIMIROVIĆ
Keyword(s):  
Genetic Algorithm ◽  
Higher Dimensions ◽  
Computational Time ◽  
Computational Results ◽  
Center Problem ◽  
Genetic Operators ◽  
Binary Coding ◽  
All Solutions ◽  
Multiple Allocation ◽  
Problem Instances

In this paper we describe a genetic algorithm (GA) for the uncapacitated multiple allocation p-hub center problem (UMApHCP). Binary coding is used and genetic operators adapted to the problem are constructed and implemented in our GA. Computational results are presented for the standard hub instances from the literature. It can be seen that proposed GA approach reaches all solutions that are proved to be optimal so far. The solutions are obtained in a reasonable amount of computational time, even for problem instances of higher dimensions.

Optimization Design and Analysis for the First Wall of CH HCSB TMB Based on Thermal Hydraulic

2013 ◽  
Vol 724-725 ◽  
pp. 681-685
Author(s):  
Hao Ran Cao ◽  
Rong Hua Huang ◽  
Jun Heng Li
Keyword(s):  
Optimization Design ◽  
Temperature Limit ◽  
Maximum Temperature ◽  
Material Base ◽  
Computational Results ◽  
First Wall ◽  
Cooling Channels ◽  
Computational Fluid Dynamics Cfd ◽  
Simulation Results ◽  
Allowable Temperature

The thermo-hydraulic performance of the first wall for CH HCSB TMB was investigated, corresponding analysis have been carried out using CFX, a computational fluid dynamics (CFD) code. The simulation results show that the maximum temperature 565°C of the FW is slightly above the allowable temperature limit 550°C of material. Base on the results so far, a modified design of the FW was presented, in which the radial-toroidal direction of cooling channels was changed to radial-poloidal. The thermo-hydraulic computational results show the temperature of the FW with modified design decrease over all, and the maximum temperature 504°C was below the allowable temperature limit for structural material. It is found that the modified design for the FW is reasonable so that the FW is effectively cooled.

scholarly journals The Ordered Clustered Travelling Salesman Problem: A Hybrid Genetic Algorithm

2014 ◽  
Vol 2014 ◽  
pp. 1-13 ◽  
Author(s):  
Zakir Hussain Ahmed
Keyword(s):  
Genetic Algorithm ◽  
Travelling Salesman Problem ◽  
Hybrid Genetic Algorithm ◽  
Computational Time ◽  
Computational Results ◽  
Travelling Salesman ◽  
Solution Quality ◽  
Heuristic Solution ◽  
Present Solution ◽  
Sequencing Problems

The ordered clustered travelling salesman problem is a variation of the usual travelling salesman problem in which a set of vertices (except the starting vertex) of the network is divided into some prespecified clusters. The objective is to find the least cost Hamiltonian tour in which vertices of any cluster are visited contiguously and the clusters are visited in the prespecified order. The problem is NP-hard, and it arises in practical transportation and sequencing problems. This paper develops a hybrid genetic algorithm using sequential constructive crossover, 2-opt search, and a local search for obtaining heuristic solution to the problem. The efficiency of the algorithm has been examined against two existing algorithms for some asymmetric and symmetric TSPLIB instances of various sizes. The computational results show that the proposed algorithm is very effective in terms of solution quality and computational time. Finally, we present solution to some more symmetric TSPLIB instances.

Symmetric Multistep Methods Revisited: II. Numerical Experiments

1999 ◽  
Vol 173 ◽  
pp. 309-314 ◽  
Author(s):  
T. Fukushima
Keyword(s):  
Multistep Methods ◽  
Computational Time ◽  
Integration Time ◽  
Implicit Methods ◽  
Symmetric Methods ◽  
Celestial Bodies ◽  
The Stability ◽  
Predictor Corrector ◽  
Symmetric Multistep Methods ◽  
Integration Errors

AbstractBy using the stability condition and general formulas developed by Fukushima (1998 = Paper I) we discovered that, just as in the case of the explicit symmetric multistep methods (Quinlan and Tremaine, 1990), when integrating orbital motions of celestial bodies, the implicit symmetric multistep methods used in the predictor-corrector manner lead to integration errors in position which grow linearly with the integration time if the stepsizes adopted are sufficiently small and if the number of corrections is sufficiently large, say two or three. We confirmed also that the symmetric methods (explicit or implicit) would produce the stepsize-dependent instabilities/resonances, which was discovered by A. Toomre in 1991 and confirmed by G.D. Quinlan for some high order explicit methods. Although the implicit methods require twice or more computational time for the same stepsize than the explicit symmetric ones do, they seem to be preferable since they reduce these undesirable features significantly.

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