Targeted multiobjective Dijkstra algorithm

Dijkstra ’ s Shortest Path Algorithm

The underlying principle of the algorithm may be described as follows: the algorithm starts with the source; it visits the vertices in order of increasing cost, and maintains a set V of visited vertices (denoted by UsedVx in the article) whose cost from the source has been computed, and a tentative cost D(u) to each unvisited vertex u. In the article, the set of all unvisited vertices is denote...

Hybrid Bellman-Ford-Dijkstra algorithm

Consider the single-source cheapest paths problem in a digraph with negative edge costs allowed. A hybrid of Bellman-Ford and Dijkstra algorithms is suggested, improving the running time bound upon Bellman-Ford for graphs with a sparse distribution of negative cost edges. The algorithm iterates Dijkstra several times without reinitializing values d(v) at vertices. At most k+2 executions of Dijk...

An Improved Dijkstra Shortest Path Algorithm

An improved Dijkstra shortest path algorithm is presented in this paper. The improved algorithm introduces a constraint function with weighted value to solve the defects of the data structure storage, such as lots of redundancy of space and time. The number of search nodes is reduced by ignoring reversed nodes and the weighted value is flexibly changed to adapt to different network complexity. ...

Dijkstra ' s Self - Stabilizing Algorithm inUnsupportive

Priority Queues and Dijkstra ’ s Algorithm ∗

We study the impact of using different priority queues in the performance of Dijkstra’s SSSP algorithm. We consider only general priority queues that can handle any type of keys (integer, floating point, etc.); the only exception is that we use as a benchmark the DIMACS Challenge SSSP code [1] which can handle only integer values for distances. Our experiments were focussed on the following: 1....