scholarly journals Rancang Bangun Sistem Penentuan Jalur Evakuasi Keluar Gedung Rumah Sakit Saat Kondisi Darurat Menggunakan Algoritma Dijkstra Dengan Antrian Prioritas

2019 ◽  
Vol 3 (01) ◽  
pp. 30-38
Author(s):  
Dody Ichwana
Keyword(s):  
Shortest Path ◽  
Shortest Paths ◽  
Priority Queue ◽  
Dijkstra Algorithm ◽  
Loss Of Life ◽  
Public Facilities ◽  
Evacuation Strategy ◽  
Evacuation Routes ◽  
Evacuation Route ◽  
Great Damage

Disaster is a sudden event, such as an accident or a natural catastrophe, that causes great damage or loss of life. Disasters can occur at any time, therefore a mechanism is needed to evacuate out of the building during a disaster. Generally public facilities have provided instructions and evacuation routes outside the building. Based on the severity of the disaster and the evacuation capability of the victim, the evacuation strategy can range from evacuation as soon as possible, evacuate slowly, move to a safe location inside the building or take refuge in the available protection room and wait for the rescue team to arrive. The algorithm for finding the shortest paths can be used to determine the evacuation route. But this path is still static, if the route damaged in then the evacuation route would become useless. The time for the evacuation process can also increase if the condition of the evacuation route is not known whether damaged or not. The solution to solve this problem is to make a system that can help find  the safest and shortest evacuation routes during emergencies. This system consist of microcontroller Arduino Mega to control the system and led for evacuation sign. The evacuation routes is determined by implementing dijkstra algorithm with priority queue to search the shortest path.

An Efficient K-Shortest Paths Based Routing Algorithm

2012 ◽  
Vol 532-533 ◽  
pp. 1775-1779
Author(s):  
Jian Lian ◽  
Yan Zhang ◽  
Cheng Jiang Li
Keyword(s):  
Computer Networks ◽  
Shortest Path ◽  
Traffic Engineering ◽  
Routing Algorithm ◽  
Shortest Paths ◽  
Routing Algorithms ◽  
Dijkstra Algorithm ◽  
Link State

We present an efficient K-shortest paths routing algorithm for computer networks. This Algorithm is based on enhancements to currently used link-state routing algorithms such as OSPF and IS-IS, which are only focusing on finding the shortest path route by adopting Dijkstra algorithm. Its desire effect to achieve is through the use of K-shortest paths algorighm, which has been implemented successfully in some fileds like traffic engineering. The correctness of this Algorithm is discussed at the same time as long as the comparison with OSPF.

scholarly journals An ImprovedPhysarum polycephalumAlgorithm for the Shortest Path Problem

2014 ◽  
Vol 2014 ◽  
pp. 1-9 ◽  
Author(s):  
Xiaoge Zhang ◽  
Qing Wang ◽  
Andrew Adamatzky ◽  
Felix T. S. Chan ◽  
Sankaran Mahadevan ◽  
...  
Keyword(s):  
Shortest Path ◽  
Shortest Paths ◽  
Unconventional Computing ◽  
Dijkstra Algorithm ◽  
Ant Colony Optimization Algorithm ◽  
Slime Mould ◽  
Inoculation Site ◽  
Biological Substrate ◽  
Approximate Shortest Path ◽  
Number Of Iterations

Shortest path is among classical problems of computer science. The problems are solved by hundreds of algorithms, silicon computing architectures and novel substrate, unconventional, computing devices. Acellular slime mouldP. polycephalumis originally famous as a computing biological substrate due to its alleged ability to approximate shortest path from its inoculation site to a source of nutrients. Several algorithms were designed based on properties of the slime mould. Many of thePhysarum-inspired algorithms suffer from a low converge speed. To accelerate the search of a solution and reduce a number of iterations we combined an original model of Physarum-inspired path solver with a new a parameter, called energy. We undertook a series of computational experiments on approximating shortest paths in networks with different topologies, and number of nodes varying from 15 to 2000. We found that the improvedPhysarumalgorithm matches well with existing Physarum-inspired approaches yet outperforms them in number of iterations executed and a total running time. We also compare our algorithm with other existing algorithms, including the ant colony optimization algorithm and Dijkstra algorithm.

scholarly journals Design and testing of a dynamic reactive signage network towards fire emergency evacuations

2020 ◽  
Vol 10 (6) ◽  
pp. 5853
Author(s):  
Christopher S. Baidal ◽  
Nestor X. Arreaga ◽  
Vladimir Sanchez Padilla
Keyword(s):  
Computer Vision ◽  
Pilot Project ◽  
Emergency Evacuation ◽  
Dijkstra Algorithm ◽  
Emergency Evacuations ◽  
Integration Of Technology ◽  
Evacuation Routes ◽  
Evacuation Route ◽  
Design And Testing ◽  
Evacuation System

The loss of several lives happens in events of natural disasters, due to the strength of nature or the static evacuation routes that usually directs towards a unique exit pathway. This paper proposes the integration of technology tools such as servers and open-source sensors into a reactive signage network to provide an updated and dynamical emergency evacuation system focusing specifically on fire situations. This pilot project works using microcontrollers that capture and manages into a server the surrounding information, setting evacuation routes and behaving according to the Dijkstra algorithm allowing the identification of obstacles or possible incidents that occur spontaneously during an evacuation. This process sends updates to the server either the evacuation route keeps the same or if a modification is required based on the information provided by the sensors about different areas, warning the shortest path for evacuation using computer vision support.

scholarly journals Computing nearest neighbour interchange distances between ranked phylogenetic trees

2021 ◽  
Vol 82 (1-2) ◽  
Author(s):  
Lena Collienne ◽  
Alex Gavryushkin
Keyword(s):  
Cancer Research ◽  
Computational Complexity ◽  
Phylogenetic Tree ◽  
Shortest Path ◽  
Phylogenetic Trees ◽  
Shortest Paths ◽  
Nearest Neighbour ◽  
Tree Inference ◽  
Subtree Prune And Regraft ◽  
Comparison Algorithms

AbstractMany popular algorithms for searching the space of leaf-labelled (phylogenetic) trees are based on tree rearrangement operations. Under any such operation, the problem is reduced to searching a graph where vertices are trees and (undirected) edges are given by pairs of trees connected by one rearrangement operation (sometimes called a move). Most popular are the classical nearest neighbour interchange, subtree prune and regraft, and tree bisection and reconnection moves. The problem of computing distances, however, is $${\mathbf {N}}{\mathbf {P}}$$ N P -hard in each of these graphs, making tree inference and comparison algorithms challenging to design in practice. Although anked phylogenetic trees are one of the central objects of interest in applications such as cancer research, immunology, and epidemiology, the computational complexity of the shortest path problem for these trees remained unsolved for decades. In this paper, we settle this problem for the ranked nearest neighbour interchange operation by establishing that the complexity depends on the weight difference between the two types of tree rearrangements (rank moves and edge moves), and varies from quadratic, which is the lowest possible complexity for this problem, to $${\mathbf {N}}{\mathbf {P}}$$ N P -hard, which is the highest. In particular, our result provides the first example of a phylogenetic tree rearrangement operation for which shortest paths, and hence the distance, can be computed efficiently. Specifically, our algorithm scales to trees with tens of thousands of leaves (and likely hundreds of thousands if implemented efficiently).

scholarly journals Dynamic Shortest Paths Methods for the Time-Dependent TSP

Algorithms ◽  
2021 ◽  
Vol 14 (1) ◽  
pp. 21
Author(s):  
Christoph Hansknecht ◽  
Imke Joormann ◽  
Sebastian Stiller
Keyword(s):  
Column Generation ◽  
Traveling Salesman Problem ◽  
Shortest Path ◽  
Valid Inequalities ◽  
Shortest Paths ◽  
Traveling Salesman ◽  
Time Dependent ◽  
Full Generality ◽  
Branching Rule ◽  
The Traveling Salesman Problem

The time-dependent traveling salesman problem (TDTSP) asks for a shortest Hamiltonian tour in a directed graph where (asymmetric) arc-costs depend on the time the arc is entered. With traffic data abundantly available, methods to optimize routes with respect to time-dependent travel times are widely desired. This holds in particular for the traveling salesman problem, which is a corner stone of logistic planning. In this paper, we devise column-generation-based IP methods to solve the TDTSP in full generality, both for arc- and path-based formulations. The algorithmic key is a time-dependent shortest path problem, which arises from the pricing problem of the column generation and is of independent interest—namely, to find paths in a time-expanded graph that are acyclic in the underlying (non-expanded) graph. As this problem is computationally too costly, we price over the set of paths that contain no cycles of length k. In addition, we devise—tailored for the TDTSP—several families of valid inequalities, primal heuristics, a propagation method, and a branching rule. Combining these with the time-dependent shortest path pricing we provide—to our knowledge—the first elaborate method to solve the TDTSP in general and with fully general time-dependence. We also provide for results on complexity and approximability of the TDTSP. In computational experiments on randomly generated instances, we are able to solve the large majority of small instances (20 nodes) to optimality, while closing about two thirds of the remaining gap of the large instances (40 nodes) after one hour of computation.

Utilizing Restricted Direction Strategy and Binary Heap Technology to Optimize Dijkstra Algorithm in WebGIS

2009 ◽  
Vol 419-420 ◽  
pp. 557-560 ◽  
Author(s):  
Rui Li
Keyword(s):  
Shortest Path ◽  
Operating Efficiency ◽  
Dijkstra Algorithm ◽  
Shortest Path Algorithm ◽  
Research Focus ◽  
Network Information ◽  
The Core ◽  
Highway Network ◽  
Core Issue ◽  
Storage Structures

Shortest path is the core issue in application of WebGIS. Improving the efficiency of the algorithm is an urgent requirement to be resolved at present. By the lossy algorithm analyzing, which is the current research focus of the shortest path algorithm to optimize, utilizing adjacency table of storage structures, restricted direction strategy and binary heap technology to optimize the algorithm, thereby reduce the scale of algorithm to improve the operating efficiency of algorithm. This scheme has been applied in the simulation of the data downloaded from the Guangdong Provincial Highway Network Information System and satisfactory results have been obtained.

scholarly journals 3D Building Evacuation Route Modelling and Visualization

2014 ◽  
Vol XL-2 ◽  
pp. 221-226 ◽  
Author(s):  
W. Chan ◽  
C. Armenakis
Keyword(s):  
Visual Representation ◽  
Multicriteria Decision Making ◽  
Building Evacuation ◽  
Emergency Responders ◽  
Spatial Risk ◽  
Risk Areas ◽  
Emergency Events ◽  
Evacuation Routes ◽  
Evacuation Route ◽  
Hierarchy Process

The most common building evacuation approach currently applied is to have evacuation routes planned prior to these emergency events. These routes are usually the shortest and most practical path from each building room to the closest exit. The problem with this approach is that it is not adaptive. It is not responsively configurable relative to the type, intensity, or location of the emergency risk. Moreover, it does not provide any information to the affected persons or to the emergency responders while not allowing for the review of simulated hazard scenarios and alternative evacuation routes. In this paper we address two main tasks. The first is the modelling of the spatial risk caused by a hazardous event leading to choosing the optimal evacuation route for a set of options. The second is to generate a 3D visual representation of the model output. A multicriteria decision making (MCDM) approach is used to model the risk aiming at finding the optimal evacuation route. This is achieved by using the analytical hierarchy process (AHP) on the criteria describing the different alternative evacuation routes. The best route is then chosen to be the alternative with the least cost. The 3D visual representation of the model displays the building, the surrounding environment, the evacuee’s location, the hazard location, the risk areas and the optimal evacuation pathway to the target safety location. The work has been performed using ESRI’s ArcGIS. Using the developed models, the user can input the location of the hazard and the location of the evacuee. The system then determines the optimum evacuation route and displays it in 3D.

scholarly journals The Effect of Route-choice Strategy on Transit Travel Time Estimates

2019 ◽  
Author(s):  
Nate Wessel ◽  
Steven Farber
Keyword(s):  
Travel Time ◽  
Shortest Path ◽  
Imperfect Information ◽  
Optimal Path ◽  
Shortest Paths ◽  
Route Choice ◽  
Travel Times ◽  
Selection Strategies ◽  
Time Estimates ◽  
Average Travel Time

Estimates of travel time by public transit often rely on the calculation of a shortest-path between two points for a given departure time. Such shortest-paths are time-dependent and not always stable from one moment to the next. Given that actual transit passengers necessarily have imperfect information about the system, their route selection strategies are heuristic and cannot be expected to achieve optimal travel times for all possible departures. Thus an algorithm that returns optimal travel times at all moments will tend to underestimate real travel times all else being equal. While several researchers have noted this issue none have yet measured the extent of the problem. This study observes and measures this effect by contrasting two alternative heuristic routing strategies to a standard shortest-path calculation. The Toronto Transit Commission is used as a case study and we model actual transit operations for the agency over the course of a normal week with archived AVL data transformed into a retrospective GTFS dataset. Travel times are estimated using two alternative route-choice assumptions: 1) habitual selection of the itinerary with the best average travel time and 2) dynamic choice of the next-departing route in a predefined choice set. It is shown that most trips present passengers with a complex choice among competing itineraries and that the choice of itinerary at any given moment of departure may entail substantial travel time risk relative to the optimal outcome. In the context of accessibility modelling, where travel times are typically considered as a distribution, the optimal path method is observed in aggregate to underestimate travel time by about 3-4 minutes at the median and 6-7 minutes at the \nth{90} percentile for a typical trip.

scholarly journals A MODIFIED GENETIC ALGORITHM FOR FINDING FUZZY SHORTEST PATHS IN UNCERTAIN NETWORKS

2016 ◽  
Vol XLI-B2 ◽  
pp. 299-304 ◽  
Author(s):  
A. A. Heidari ◽  
M. R. Delavar
Keyword(s):  
Genetic Algorithm ◽  
Shortest Path ◽  
Shortest Paths ◽  
The Body ◽  
Shortest Path Problems ◽  
Conventional Procedure ◽  
Path Lengths ◽  
The Cost ◽  
Uncertain Networks ◽  
Exploration Exploitation

In realistic network analysis, there are several uncertainties in the measurements and computation of the arcs and vertices. These uncertainties should also be considered in realizing the shortest path problem (SPP) due to the inherent fuzziness in the body of expert's knowledge. In this paper, we investigated the SPP under uncertainty to evaluate our modified genetic strategy. We improved the performance of genetic algorithm (GA) to investigate a class of shortest path problems on networks with vague arc weights. The solutions of the uncertain SPP with considering fuzzy path lengths are examined and compared in detail. As a robust metaheuristic, GA algorithm is modified and evaluated to tackle the fuzzy SPP (FSPP) with uncertain arcs. For this purpose, first, a dynamic operation is implemented to enrich the exploration/exploitation patterns of the conventional procedure and mitigate the premature convergence of GA technique. Then, the modified GA (MGA) strategy is used to resolve the FSPP. The attained results of the proposed strategy are compared to those of GA with regard to the cost, quality of paths and CPU times. Numerical instances are provided to demonstrate the success of the proposed MGA-FSPP strategy in comparison with GA. The simulations affirm that not only the proposed technique can outperform GA, but also the qualities of the paths are effectively improved. The results clarify that the competence of the proposed GA is preferred in view of quality quantities. The results also demonstrate that the proposed method can efficiently be utilized to handle FSPP in uncertain networks.

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