Applications of the Dijkstra’s Algorithm part1(Computer Science)
1.Search and Rescue in a Maze-like Environment with Ant and Dijkstra Algorithms(arXiv)
Author : Z. Husain, A. Al Zaabi, H. Hildmann, F. Saffre, D. Ruta, A. F. Isakovic
Abstract : With the growing reliability of modern Ad Hoc Networks, it is encouraging to analyze potential involvement of autonomous Ad Hoc agents in critical situations where human involvement could be perilous. One such critical scenario is the Search and Rescue effort in the event of a disaster where timely discovery and help deployment is of utmost importance. This paper demonstrates the applicability of a bio-inspired technique, namely Ant Algorithms (AA), in optimizing the search time for a near optimal path to a trapped victim, followed by the application of Dijkstra’s algorithm in the rescue phase. The inherent exploratory nature of AA is put to use for a faster mapping and coverage of the unknown search space. Four different AA are implemented, with different effects of the pheromone in play. An inverted AA, with repulsive pheromones, was found to be the best fit for this particular application. After considerable exploration, upon discovery of the victim, the autonomous agents further facilitate the rescue process by forming a relay network, using the already deployed resources. Hence, the paper discusses a detailed decision making model of the swarm, segmented into two primary phases, responsible for the search and rescue respectively. Different aspects of the performance of the agent swarm are analyzed, as a function of the spatial dimensions, the complexity of the search space, the deployed search group size, and the signal permeability of the obstacles in the area
2. Targeted Multiobjective Dijkstra Algorithm(arXiv)
Author : Pedro Maristany de las Casas, Luitgard Kraus, Antonio Sedeño-Noda, Ralf Borndörfer
Abstract : In this paper, we introduce the Targeted Multiobjective Dijkstra Algorithm (T-MDA), a label setting algorithm for the One-to-One Multiobjective Shortest Path (MOSP) Problem. The T-MDA is based on the recently published Multiobjective Dijkstra Algorithm (MDA) and equips it with A*-like techniques. The resulting speedup is comparable to the speedup that the original A* algorithm achieves for Dijkstra’s algorithm. Unlike other methods from the literature, which rely on special properties of the biobjective case, the T-MDA works for any dimension. To the best of our knowledge, it gives rise to the first efficient implementation that can deal with large scale instances with more than two objectives. A version tuned for the biobjective case, the T-BDA, outperforms state-of-the-art methods on almost every instance of a standard benchmark testbed that is not solvable in fractions of a second
3. Using Recursive KMeans and Dijkstra Algorithm to Solve CVRP(arXiv)
Author : Hassan Moussa
Abstract : Capacitated vehicle routing problem (CVRP) is being one of the most common optimization problems in our days, considering the wide usage of routing algorithms in multiple fields such as transportation domain, food delivery, network routing, … Capacitated vehicle routing problem is classified as an NP-Hard problem, hence normal optimization algorithm can’t solve it. In our paper, we discuss a new way to solve the mentioned problem, using a recursive approach of the most known clustering algorithm “K-Means”, one of the known shortest path algorithm “Dijkstra”, and some mathematical operations. In this paper, we will show how to implement those methods together in order to get the nearest solution of the optimal route, since research and development are still on go, this research paper may be extended with another one, that will involve the implementational results of this thoric side.
