Maximum Flows by Incremental Breadth-First Search

2011 ◽  
pp. 457-468 ◽  
Author(s):  
Andrew V. Goldberg ◽  
Sagi Hed ◽  
Haim Kaplan ◽  
Robert E. Tarjan ◽  
Renato F. Werneck
Keyword(s):  
Breadth First Search ◽  
Maximum Flows

Computer algorithms

2018 ◽  
Author(s):  
Mark Newman
Keyword(s):  
Data Structures ◽  
Analysis Of Algorithms ◽  
Shortest Paths ◽  
Minimum Cut ◽  
Network Data ◽  
Computer Algorithms ◽  
Breadth First Search ◽  
Augmenting Path ◽  
Basic Concepts ◽  
Maximum Flows

This chapter introduces some of the fundamental concepts of numerical network calculations. The chapter starts with a discussion of basic concepts of computational complexity and data structures for storing network data, then progresses to the description and analysis of algorithms for a range of network calculations: breadth-first search and its use for calculating shortest paths, shortest distances, components, closeness, and betweenness; Dijkstra's algorithm for shortest paths and distances on weighted networks; and the augmenting path algorithm for calculating maximum flows, minimum cut sets, and independent paths in networks.

Tidal Flow: A Fast and Teachable Maximum Flow Algorithm

2018 ◽  
Vol 12 ◽  
pp. 25-41
Author(s):  
Matthew C. FONTAINE
Keyword(s):  
Computer Science ◽  
Tidal Flow ◽  
Maximum Flow ◽  
Efficient Algorithms ◽  
Science Students ◽  
Flow Algorithm ◽  
Maximum Flows

Among the most interesting problems in competitive programming involve maximum flows. However, efficient algorithms for solving these problems are often difficult for students to understand at an intuitive level. One reason for this difficulty may be a lack of suitable metaphors relating these algorithms to concepts that the students already understand. This paper introduces a novel maximum flow algorithm, Tidal Flow, that is designed to be intuitive to undergraduate andpre-university computer science students.

Algoritma Perencanaan Jalur Kendaraan Otonom berbasis Hibridisasi Algoritma BFS dan Path Smoothing

2020 ◽  
Vol 8 (1) ◽  
pp. 13-22
Author(s):  
Muhammad Aria
Keyword(s):  
Breadth First Search ◽  
Search Path ◽  
Path Smoothing

Abstrak – Pada penelitian ini dirancang algoritma alternatif untuk perencanaan jalur kendaraan otonom. Algoritma yang diusulkan adalah hibridisasi dari algoritma Breadth First Search (BFS) dan algoritma path smoothing (BFS – path smoothing). Berdasarkan pengamatan dari hasil pengujian, keuntungan dari algoritma BFS adalah dapat memberikan solusi yang menuju solusi optimal, tetapi memiliki kelemahan dari waktu komputasi yang tinggi. Agar diperoleh solusi yang optimal, maka jalur yang dihasilkan oleh algoritma BFS akan diproses lebih lanjut oleh algoritma path smoothing. Walaupun algoritma BFS - path smoothing memiliki waktu komputasi yang tinggi, tetapi untuk tujuan mendapatkan solusi yang optimal, waktu komputasi BFS – path smoothing masih lebih rendah daripada algoritma RRT* untuk mendapatkan solusi yang optimal. Algoritma RRT* adalah salah satu algoritma yang umum digunakan untuk perencanaan jalur pada kendaraan otonom. Proses hibridisasi ini dilakukan dengan cara menjalankan algoritma BFS terlebih dahulu untuk memberikan solusi awal. Solusi awal tersebut kemudian ditingkatkan kualitasnya menggunakan algoritma path smoothing untuk memperoleh solusi yang optimal. Pengujian algoritma BFS-path smoothing ini dilakukan secara simulasi menggunakan beberapa kasus benchmark yang ada, yaitu lingkungan narrow, maze, trap dan clutter. Kriteria optimalitas yang dibandingkan adalah biaya jalur dan waktu komputasi. Pada pengujian, performansi dari algoritma BFS-path smoothing dibandingkan dengan performansi dari algoritma RRT*. Kami menunjukkan bahwa algoritma yang diusulkan dapat menghasilkan output jalur dengan kualitas yang lebih tinggi daripada jalur yang diproduksi oleh RRT*.   Kata Kunci : Beadth First Search, path smoothing, perencanaan jalur, pengujian simulasi, RRT*

Restricted Constraints in the Problem of Maximum Attainable Flow in Minimum Cost in a Network

2015 ◽  
Vol 3 (2) ◽  
Author(s):  
Nazimuddin Ahmed ◽  
Shobha Duttadeka
Keyword(s):  
Minimum Cost ◽  
Optimal Route ◽  
Precedence Relation ◽  
Flow Capacity ◽  
Cost Distance ◽  
Realistic Situation ◽  
Maximum Flows

In this paper we have considered a version of restricted constraints in the problem of maximum attainable flow (capacity) in minimum cost (distance) in a network (Ahmed, Das, & Purusotham, 2012b). By restricted constraints one means that the link(s) (cities or stations or nodes) are completed (or visited) in such a way that a particular link is to be preceded (completed or visited) by another link (precedence relation need not be immediate). Here the aim is to obtained an optimal route of a more realistic situation as to scheduling a restricted constraints to a maximum flows at a minimum cost from a source to a destination. The distance (cost) and arc capacity between any two stations are given.

Network search

2018 ◽  
Author(s):  
Mark Newman
Keyword(s):  
Web Search ◽  
Distributed Databases ◽  
Small World ◽  
Peer Networks ◽  
Model Parameters ◽  
Breadth First Search ◽  
Ranking Algorithms ◽  
Network Search ◽  
Peer To Peer Networks ◽  
Search Processes

This chapter gives a discussion of search processes on networks. It begins with a discussion of web search, including crawlers and web ranking algorithms such as PageRank. Search in distributed databases such as peer-to-peer networks is also discussed, including simple breadth-first search style algorithms and more advanced “supernode” approaches. Finally, network navigation is discussed at some length, motivated by consideration of Milgram's letter passing experiment. Kleinberg's variant of the small-world model is introduced and it is shown that efficient navigation is possible only for certain values of the model parameters. Similar results are also derived for the hierarchical model of Watts et al.

scholarly journals Safe Path Planning Algorithms for Mobile Robots Based on Probabilistic Foam

Sensors ◽  
2021 ◽  
Vol 21 (12) ◽  
pp. 4156
Author(s):  
Luís B. P. Nascimento ◽  
Dennis Barrios-Aranibar ◽  
Vitor G. Santos ◽  
Diego S. Pereira ◽  
William C. Ribeiro ◽  
...  
Keyword(s):  
Path Planning ◽  
Mobile Robots ◽  
Configuration Space ◽  
Autonomous Robot ◽  
Breadth First Search ◽  
Propagation Process ◽  
Robot Systems ◽  
And Performance ◽  
Safe Path ◽  
High Clearance

The planning of safe paths is an important issue for autonomous robot systems. The Probabilistic Foam method (PFM) is a planner that guarantees safe paths bounded by a sequence of structures called bubbles that provides safe regions. This method performs the planning by covering the free configuration space with bubbles, an approach analogous to a breadth-first search. To improve the propagation process and keep the safety, we present three algorithms based on Probabilistic Foam: Goal-biased Probabilistic Foam (GBPF), Radius-biased Probabilistic Foam (RBPF), and Heuristic-guided Probabilistic Foam (HPF); the last two are proposed in this work. The variant GBPF is fast, HPF finds short paths, and RBPF finds high-clearance paths. Some simulations were performed using four different maps to analyze the behavior and performance of the methods. Besides, the safety was analyzed considering the new propagation strategies.

Indoor landmark-based path-finding utilising the expanded connectivity of an endpoint partition

2016 ◽  
Vol 45 (2) ◽  
pp. 233-252
Author(s):  
Pepijn Viaene ◽  
Alain De Wulf ◽  
Philippe De Maeyer
Keyword(s):  
Visual Information ◽  
Spatial Configuration ◽  
Shortest Paths ◽  
Minimal Amount ◽  
Path Finding ◽  
Breadth First Search ◽  
Length Increase ◽  
Efficient Communication ◽  
Indoor Wayfinding

Landmarks are ideal wayfinding tools to guide a person from A to B as they allow fast reasoning and efficient communication. However, very few path-finding algorithms start from the availability of landmarks to generate a path. In this paper, which focuses on indoor wayfinding, a landmark-based path-finding algorithm is presented in which the endpoint partition is proposed as spatial model of the environment. In this model, the indoor environment is divided into convex sub-shapes, called e-spaces, that are stable with respect to the visual information provided by a person’s surroundings (e.g. walls, landmarks). The algorithm itself implements a breadth-first search on a graph in which mutually visible e-spaces suited for wayfinding are connected. The results of a case study, in which the calculated paths were compared with their corresponding shortest paths, show that the proposed algorithm is a valuable alternative for Dijkstra’s shortest path algorithm. It is able to calculate a path with a minimal amount of actions that are linked to landmarks, while the path length increase is comparable to the increase observed when applying other path algorithms that adhere to natural wayfinding behaviour. However, the practicability of the proposed algorithm is highly dependent on the availability of landmarks and on the spatial configuration of the building.

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