Killer Whale Algorithm for Solving the Maximum Flow Problem on Transportation Networks

Afaf Edinat; Mohammad Shehab; Fatima Haimour; Hanaa Fathi; Katrina Sundus

doi:10.47852/bonviewJCCE52026863

Authors

Afaf Edinat College of Information Technology, Amman Arab University, Jordan
Mohammad Shehab College of Information Technology, Amman Arab University, Jordan https://orcid.org/0000-0003-0211-3503
Fatima Haimour College of Information Technology, Zarqa University, Jordan
Hanaa Fathi College of Information Technology, Amman Arab University, Jordan
Katrina Sundus Faculty of Science and Information Technology, Al-Zaytooneh University of Jordan, Jordan https://orcid.org/0000-0002-2542-282X

DOI:

https://doi.org/10.47852/bonviewJCCE52026863

Keywords:

traffic congestion, transportation problem, max flow problem, meta-heuristic algorithms, killer whale algorithm

Abstract

The most extreme stream issue (MFP) may be a principal subject in the chart hypothesis with applications in computer science, operations inquiry, and designing. It plays a key part in ranges such as activity control, communication frameworks, and the dissemination of assets. Classical calculations, especially Ford–Fulkerson and its expansions, have given the establishment of the means for tackling this issue. In any case, when systems develop bigger, more complex, or dynamically alter, these approaches regularly battle to preserve effectiveness and accuracy. Much like transportation frameworks, each course in an arrangement encompasses a capacity restraint, confining how much stream can move between hubs. Conventional strategies, which accept settled structures and unsurprising imperatives, are not continuously suited to taking care of these challenges. To deal with these limits, this think piece shows the Killer Whale Optimization (KWO) calculation; it is pushed by the chasing methods of killer whales. The strategy was based on multi-flow problems using real and made-up datasets. To show its useful meaning, a case study was made on a project stream in Kota Kinabalu, where made-up systems of different sizes were used to test flexibility and reliability. The result seems like KWO usually beats the Ford–Fulkerson method, especially because it does faster merging and shows more flexibility when dealing with complicated stream situations. These advantages make KWO a good choice for real world stream optimization problems. Beyond theoretical interest, the results suggest that the calculation may be used for project management, transport planning, and resource assignment in various organized systems.

Received: 19 July 2025 | Revised: 18 September 2025 | Accepted: 22 October 2025

Conflicts of Interest

The authors declare that they have no conflicts of interest to this work.

Data Availability Statement

Data are available from the corresponding author upon reasonable request.

Author Contribution Statement

Afaf Edinat: Conceptualization, Methodology, Software, Validation, Formal analysis, Investigation, Data curation, Writing – original draft, Writing – review & editing, Visualization, Supervision, Project administration. Mohammad Shehab: Conceptualization, Methodology, Software, Validation, Formal analysis, Investigation, Data curation, Writing – original draft, Writing – review & editing, Supervision, Project administration. Fatima Haimour: Methodology, Validation, Formal analysis, Data curation, Writing – original draft, Writing – review & editing, Supervision. Hanaa Fathi: Conceptualization, Software, Formal analysis, Data curation, Writing – original draft, Writing – review & editing, Visualization, Supervision. Katrina Sundus: Software, Validation, Writing – original draft, Writing – review & editing.