Rami Halloush · International Journal of Communication Networks and Distributed Systems · 2016
In multicasting, there is a need to efficiently specify the paths connecting a source node to the different destination nodes. A common method to achieve that is to use a shortest-path tree (SPT) algorithm, such as Dijkstra%s algorithm. A multicasting application, however, that is intended for a multi-hop wireless network should be designed in a way that considers the characteristics of such network. One important characteristic is overhearing, which means that a transmission from one node could be heard by many nodes other than the intended receiver. We propose modifying Dijkstra%s algorithm to take advantage of overhearing. As opposed to the conventional Dijkstra%s algorithm where path costs used to build an SPT remain fixed during the course of the algorithm, we propose estimating the overhearing opportunities at each iteration of the algorithm and modifying path costs accordingly. Simulation results demonstrate up to 68% throughput enhancement over the conventional Dijkstra's algorithm.
Cited by 4
Siva Prasad Behera, Prasanta Kumar Raut · International Journal of Reasoning-based Intelligent Systems · 2023
The shortest path problem is a fundamental problem in network analysis, and many algorithms have been developed to solve it efficiently. One of the most widely used algorithms is Dijkstra's algorithm, which finds the shortest path between two nodes in a graph. Recently, spherical neutrosophic numbers (SNNs) have emerged as a powerful tool for handling uncertain information in network domains. In this study, we propose a modified version of Dijkstra's algorithm that uses SNNs to handle uncertainty in edge weights in a network. The edge weights are represented as SNNs to account for uncertainty in the distances between vertices, and the algorithm is modified to handle the arithmetic operations of SNNs and update distances and priorities accordingly. Our results show that the algorithm can effectively handle uncertainty in the network domain and find the shortest path between two nodes with high accuracy.
Cited by 0
Prasanta Kumar Raut, Siva Prasad Behera · International Journal of Reasoning-based Intelligent Systems · 2025
The shortest path problem is a fundamental problem in network analysis, and many algorithms have been developed to solve it efficiently. One of the most widely used algorithms is Dijkstra's algorithm, which finds the shortest path between two nodes in a graph. Recently, spherical neutrosophic numbers (SNNs) have emerged as a powerful tool for handling uncertain information in network domains. In this study, we propose a modified version of Dijkstra's algorithm that uses SNNs to handle uncertainty in edge weights in a network. The edge weights are represented as SNNs to account for uncertainty in the distances between vertices, and the algorithm is modified to handle the arithmetic operations of SNNs and update distances and priorities accordingly. Our results show that the algorithm can effectively handle uncertainty in the network domain and find the shortest path between two nodes with high accuracy.
Cited by 0
Kawtar Jellid, Tomader Mazri · International Journal of Advanced Computer Science and Applications · 2023
This research article proposes an algorithm for improving the ITS-G5 protocol, which addresses the issue of response time. The algorithm includes the integration of Dijkstra's algorithm to prioritize shorter paths for message transmission, resulting in reduced delays. The initial algorithm for the ITS-G5 protocol is presented, followed by the modified algorithm that incorporates Dijkstra's algorithm. The modified algorithm utilizes a node-based approach and implements Dijkstra's algorithm to find the shortest path between two nodes. The algorithm is evaluated in a scenario involving 20 vehicles, where each vehicle has its own message. The results show improved communication efficiency and reduced response time compared to the original ITS-G5 protocol.
Cited by 0Open access
Kaicong Wei, Ying Gao, Wei Zhang et al. · 2019
Path optimization is especially useful for improving freight efficiency, and the problem of finding the maximum load path is an important issue in path optimization. Although the problem of finding the shortest path is similar to the problem of finding the maximum load path, the Dijkstra's algorithm for solving the problem of finding the shortest path is not suitable for solving the problem of finding the maximum load path. In this paper, the Dijkstra's algorithm for solving the problem of finding the shortest path is introduced, and the Dijkstra's algorithm is modified to solve the problem of finding the maximum load path. Finally, the running process of the modified Dijkstra's algorithm is described by an example.
Cited by 34
Uchenna Ewa Mba, N. Njideka Mbeledogu · IJARCCE · 2024
In recent times, the problems of efficiency and marginal productivity in the air transportation industry have become one of a global concern, particularly, in Nigeria. Safer and faster movement of passengers and their luggages in a record time with drastic reduction in the running cost are bottlenecks facing the aviation industry. The Traditional Dijkstra's Algorithm could determine shortest path in air route distance but its exiting mechanism leads it to infinite loop. Based on this, the research sought to deploy Modified Dijkstra's Algorithm in the planning, calculation and implementation of air route network to determine the shortest path distance. The approach employed the Comparison Addition Model (CAM) in determining the optimal distance from the source to the destination within the network. Permutation and combination analysis was used to determine all possible routes. Multiple parameters (time factor optimization, congestion reduction, memory utilization) capable of determining the shortest and optimal distance a flight can possibly travel in a routing network were handled. Python Programming Language was proficient for its coding. The performance evaluation of Modified Dijkstra's Algorithm and Traditional Dijkstra's algorithm based on F_1 Score, Recall and Precision was carried. The Modified Dijkstra's Algorithm was found to perform better than the Traditional Dijkstra's Algorithm.
Cited by 0Open access
Ankit Sahu, Aman Singh, Aman Yadav · 2021
We review recent advances in public transport route planning algorithms the modified dijkstra algorithm. However, the ideal route for public transport differs depending on the traveller's choice. The shortest route is preferred by most users as the primary criteria for the ideal route. According to our research, Dijkstra's algorithm is mainly used to find the shortest path from a single source to all other nodes of a weighted graph. However, Dijkstra's algorithm is inefficient for planning public transport routes, because it ignores the number of transfers and walking distances. Thus, in order to minimize these drawbacks, Dijkstra's algorithm is modified. It can be seen that our modified algorithm is quite efficient for route planning in the public transport network in terms of the number of transfers, the distance of the proposed route and the walking distance.
Cited by 0
Н. И. Листопад, И. А. Карук, A. A. Hayder · RePEc: Research Papers in Economics · 2016
The article presents an overview of the main trends and methods of searching the shortest path information transmission in the telecommunications networks. The basic algorithms and their modifications are described. Special attention is given to the modified Dijkstra's algorithm that takes into account QoS requirements. The modified algorithm and its UML diagram are presented.
Cited by 0Open access
Bruce Golden, Michael O. Ball · Networks · 1978
Abstract This paper considers the problem of finding the shortest path between an origin and destination pair in networks whose arc lengths are Euclidean distances. Dijkstra's algorithm and a modified version of Dijkstra's algorithm which is more adaptive to network topology are compared. We demonstrate on the infinite lattice network with diagonal arcs (a prototype of more general sparse Euclidean networks) that on the average the adaptive algorithm expands less than 8.3% the area that would be expanded by the Dijkstra algorithm and in the worst case it expands less than 10.7%. In addition, we present computational results for more general networks.
Cited by 33
Niemeyer, Kyle E., Sung, Chih-Jen · arXiv (Cornell University) · 2016
The importance of graph search algorithm choice to the directed relation graph with error propagation (DRGEP) method is studied by comparing basic and modified depth-first search, basic and R-value-based breadth-first search (RBFS), and Dijkstra's algorithm. By using each algorithm with DRGEP to produce skeletal mechanisms from a detailed mechanism for n-heptane with randomly-shuffled species order, it is demonstrated that only Dijkstra's algorithm and RBFS produce results independent of species order. In addition, each algorithm is used with DRGEP to generate skeletal mechanisms for n-heptane covering a comprehensive range of autoignition conditions for pressure, temperature, and equivalence ratio. Dijkstra's algorithm combined with a coefficient scaling approach is demonstrated to produce the most compact skeletal mechanism with a similar performance compared to larger skeletal mechanisms resulting from the other algorithms. The computational efficiency of each algorithm is also compared by applying the DRGEP method with each search algorithm on the large detailed mechanism for n-alkanes covering n-octane to n-hexadecane with 2115 species and 8157 reactions. Dijkstra's algorithm implemented with a binary heap priority queue is demonstrated as the most efficient method, with a CPU cost two orders of magnitude less than the other search algorithms.
Cited by 0Open access
Tianxu Zhang, Xin Li, Yongli Zhao et al. · 2025
We propose the Modified Contraction Hierarchy (MCH) algorithm, a fast routing solution for optical networks that enables rapid path reconstruction under single-link failures. The MCH employs a hierarchical pruning mechanism that dynamically shrinks the search space. Simulations demonstrate significantly faster recovery than Dijkstra's algorithm. ©2025 The Author(s)
Cited by 0
Roden B. Pelegrino, Kristine T. Soberano · INTERNATIONAL JOURNAL OF MULTIDISCIPLINARY RESEARCH AND ANALYSIS · 2025
This study addresses the challenges of path optimization in rural settings, particularly villages, by integrating dijkstra's algorithm with precision geo-mapping technologies. Key features include an interactive interface for real-time path visualization, and predictive analytics for anticipating disruptions. This research seeks to improve navigation and resource management to local communities, government agencies, urban planners, emergency services, and future researchers. The study's participants, comprising 50 individuals from balasan, iloilo, encompassed residents, emergency responders, and visitors. This study employs a quantitative research approach to systematically gather and analyze numerical data. The findings from the study demonstrate that the modified dijkstra's algorithm effectively adapts to rural environments, addressing unique spatial and infrastructural challenges. Geographic information systems and advanced spatial analysis tools provide detailed maps crucial for accurate pathfinding, enhanced by an interactive interface for real-time updates and predictive analytics for proactive path management. Overall, the system achieved high ratings across iso 25010 standards, indicating strong performance, usability, reliability, and user satisfaction in optimizing paths within villages. The study concludes that the system, utilizing a modified dijkstra's algorithm, mapping tools, interactive visualization, and predictive analytics, significantly improves pathfinding and navigation efficiency in rural areas of balasan, iloilo. It has demonstrated strong acceptability and usability across multiple metrics, highlighting its potential benefit for local communities. Based on the study's findings, recommendations include refining dijkstra's algorithm for rural terrains, enhancing predictive analytics with advanced machine learning, developing multi-criteria optimization algorithms, expanding the system's application beyond villages, establishing monitoring frameworks, and fostering ongoing research for continuous improvement.
Cited by 0Open access
Carlos Santiago, Bodhisattwa Gangopadhyay, João Pedro · 2011
In order to reduce the costs associated with network planning, this paper presents a tool tailored for Radio over Fibre networks that: determines the location of antennas to cover a Manhattan like scenario considering candidate sites at different heights, for example on top of building or on street lamp posts; defines the number and location of optical splitters; determines the amount of fibre required for the deployment; and defines the path that reduces conduit usage. In this paper, we also describe the algorithms developed for this tool, including an algorithm to divide the deployment area, an algorithm to define the location of the optical splitters and a modified Dijkstra's algorithm to find the shortest path that also reduces the amount of conduits. The main outcomes of a study comprising different scenarios are that there is no significant fibre savings from supporting more than 10 antennas per optical splitter and that the modified Dijkstra's algorithm allows saving more than 20% in length of conduits.
Cited by 1
Roden B. Pelegrino Jr., Kristine T. Soberano, PhD. · Zenodo (CERN European Organization for Nuclear Research) · 2025
This study addresses the challenges of path optimization in rural settings, particularly villages, by integrating dijkstra's algorithm with precision geo-mapping technologies. Key features include an interactive interface for real-time path visualization, and predictive analytics for anticipating disruptions. This research seeks to improve navigation and resource management to local communities, government agencies, urban planners, emergency services, and future researchers. The study's participants, comprising 50 individuals from balasan, iloilo, encompassed residents, emergency responders, and visitors. This study employs a quantitative research approach to systematically gather and analyze numerical data. The findings from the study demonstrate that the modified dijkstra's algorithm effectively adapts to rural environments, addressing unique spatial and infrastructural challenges. Geographic information systems and advanced spatial analysis tools provide detailed maps crucial for accurate pathfinding, enhanced by an interactive interface for real-time updates and predictive analytics for proactive path management. Overall, the system achieved high ratings across iso 25010 standards, indicating strong performance, usability, reliability, and user satisfaction in optimizing paths within villages. The study concludes that the system, utilizing a modified dijkstra's algorithm, mapping tools, interactive visualization, and predictive analytics, significantly improves pathfinding and navigation efficiency in rural areas of balasan, iloilo. It has demonstrated strong acceptability and usability across multiple metrics, highlighting its potential benefit for local communities. Based on the study's findings, recommendations include refining dijkstra's algorithm for rural terrains, enhancing predictive analytics with advanced machine learning, developing multi-criteria optimization algorithms, expanding the system's application beyond villages, establishing monitoring frameworks, and fostering ongoing research for continuous improvement.
Cited by 0Open access
D. Goswami, Sathi Mukherjee · International Journal of Engineering in Computer Science · 2024
Hesitant fuzzy set theory is a branch of fuzzy set theory that uses new measures to address uncertainty in shortest path problems. In this paper, we propose a generalized version of Dijkstra's algorithm from source node to destination node for scenarios where each edge has an associated hesitant fuzzy number as its cost. The Bonferroni mean (BM) is indeed a useful tool in multi-criteria decision-making (MCDM) because it effectively captures the interrelationships among different criteria or arguments. We introduce a modified hesitant fuzzy Dijkstra's algorithm (MHFDA) to address hesitant fuzzy shortest path problems (HFSPP). This algorithm utilizes hesitant fuzzy Bonferroni means (HFBM) and hesitant fuzzy weighted geometric operators (HFWG) to find the solution.
Cited by 0Open access
Roden B. Pelegrino Jr., Kristine T. Soberano, PhD. · Zenodo (CERN European Organization for Nuclear Research) · 2025
This study addresses the challenges of path optimization in rural settings, particularly villages, by integrating dijkstra's algorithm with precision geo-mapping technologies. Key features include an interactive interface for real-time path visualization, and predictive analytics for anticipating disruptions. This research seeks to improve navigation and resource management to local communities, government agencies, urban planners, emergency services, and future researchers. The study's participants, comprising 50 individuals from balasan, iloilo, encompassed residents, emergency responders, and visitors. This study employs a quantitative research approach to systematically gather and analyze numerical data. The findings from the study demonstrate that the modified dijkstra's algorithm effectively adapts to rural environments, addressing unique spatial and infrastructural challenges. Geographic information systems and advanced spatial analysis tools provide detailed maps crucial for accurate pathfinding, enhanced by an interactive interface for real-time updates and predictive analytics for proactive path management. Overall, the system achieved high ratings across iso 25010 standards, indicating strong performance, usability, reliability, and user satisfaction in optimizing paths within villages. The study concludes that the system, utilizing a modified dijkstra's algorithm, mapping tools, interactive visualization, and predictive analytics, significantly improves pathfinding and navigation efficiency in rural areas of balasan, iloilo. It has demonstrated strong acceptability and usability across multiple metrics, highlighting its potential benefit for local communities. Based on the study's findings, recommendations include refining dijkstra's algorithm for rural terrains, enhancing predictive analytics with advanced machine learning, developing multi-criteria optimization algorithms, expanding the system's application beyond villages, establishing monitoring frameworks, and fostering ongoing research for continuous improvement.
Cited by 0Open access
Ittner Alexandre Erwin, Daniel S César, Sasse Fernando Deeke · Frontiers in artificial intelligence and applications · 2009
In this paper, we present new results concerning the heuristic optimization of cable routing in electrical panels. The problem is modeled and a heuristic solution, using an insertion algorithm and a modified version of the Dijkstra's algorithm, is proposed, analyzed, and compared with human-made solutions. Tests have shown that good results can be obtained from layouts commonly found in the industry.
Cited by 2
Petrášová, Tereza · Digital Repository (National Repository of Grey Literature) · 2018
Title: On the Dijkstra's algorithm in the Pedestrian Flow Problem Author: Tereza Petrášová Department: Department of Numerical Mathematics Supervisor: doc. RNDr. Jiří Felcman, CSc., Department of Numerical Mathe- matics Abstract: The pedestrian flow problem is described by a coupled system of the first order hyperbolic partial differential equations with the source term and by the functional minimization problem for the desired direction of motion. The functional minimization is based on the modified Dijkstra's algorithm used to find the minimal path to the exit. The original modification of the Dijkstra's algorithm is proposed to increase its efficiency in the pedestrian flow problem. This approach is compared with the algorithm of Bornemann and Rasch for determination of the desired direction of motion based on the solution of the so- called Eikonal equation. Both approaches are numerically tested in the framework of two splitting algorithms for solution of the coupled problem. The former splitting algorithm is based on the finite volume method yielding for the given time instant the piecewise constant approximation of the solution. The latter one uses the implicit discretization by a space-time discontinuous Galerkin method based on the discontinuous piecewise polynomial approximation. The numerical examples...
Cited by 0
Prima Wiratama, Ary Mazharuddin Shiddiqi · JUTI Jurnal Ilmiah Teknologi Informasi · 2021
Emergency Aid has a very vital role in saving the patient's life. The emergency process involves two stages, namely the pre-hospital and the hospital stage. Striving for the entire emergency process is to have the fastest response time. The initial part of emergency treatment (pre-hospital) is determining the shortest and fastest route to the hospital. In addition, the availability of the targeted hospital must also be considered. We modified Dijkstra's Algorithm to produce the shortest route and the fastest time by considering the availability of the targeted hospital to support the handling of the emergency process. The modification made to the Dijkstra algorithm replaces the weight of Dijkstra's distance with a quantity representing the congestion rate and distance. Besides, the event time is estimated to determine the status of the intended hospital. As a result, Dijkstra's modification method can produce a more efficient and faster route.
Cited by 0Open access
Tereza Petrášová · Digital Repository (National Repository of Grey Literature) · 2018
Title: On the Dijkstra's algorithm in the Pedestrian Flow Problem Author: Tereza Petrášová Department: Department of Numerical Mathematics Supervisor: doc. RNDr. Jiří Felcman, CSc., Department of Numerical Mathe- matics Abstract: The pedestrian flow problem is described by a coupled system of the first order hyperbolic partial differential equations with the source term and by the functional minimization problem for the desired direction of motion. The functional minimization is based on the modified Dijkstra's algorithm used to find the minimal path to the exit. The original modification of the Dijkstra's algorithm is proposed to increase its efficiency in the pedestrian flow problem. This approach is compared with the algorithm of Bornemann and Rasch for determination of the desired direction of motion based on the solution of the so- called Eikonal equation. Both approaches are numerically tested in the framework of two splitting algorithms for solution of the coupled problem. The former splitting algorithm is based on the finite volume method yielding for the given time instant the piecewise constant approximation of the solution. The latter one uses the implicit discretization by a space-time discontinuous Galerkin method based on the discontinuous piecewise polynomial approximation. The numerical examples...
Cited by 0