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Journal of Information and Optimization Sciences cover
Hybrid ·Peer-reviewed·ISSN (Online): 2169-0103·ISSN (Print): 0252-2667

WoS  JIF 2026 : 0.4 (Q4)

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Monthly Journal: Publishes theoretical and applied research on topics in information and optimization sciences.

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Open Access Research Article

Local and global information in online stochastic shortest path problem and competitive analysis

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pp. 2111–2127Vol. 46Issue 7October 2025DOI: 10.47974/JIOS-1584XML
Received:
11 Jul 2023
Published Online:
03 Feb 2025
Article type:
Research Article
Language:
EN
Article no.:
JIOS-1584
Pages:
2111–2127

Abstract

In the online shortest path problem, the arc costs are the online parameters in a network and their values are not known for decision-makers in advance. So, the online decisions are made by arriving any node and with respect to some statistical information of the leaving nodes and not by the realization of the arc costs; however, the decisions for the traversed paths are not changed or rejected, and they are established permanently. The online decision criteria are defined as expected path lengths related to the available statistical information in the online manner. The online expected stochastic shortest path lengths are computed by two novel online adapted formulas. Then, the competitive analyses are presented for the obtained online stochastic optimal solution against the offline optimal solution. The expected competitive ratios are revealed differences between the application of some local and global information, so that it shows e–2 improvement for the local statistical information against the globalb statistical information, relatively. Numerical results and the average case analyses compared the obtained formulas as the online optimality indices. The formulas are applied in both acyclic and cyclic networks, and the obtained competitive ratios are verified by some numerical examples.

Keywords

Subject Classifications

90C2790C59

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