Asia Mathematika, Vol 10, issue 1, pages: 64--72.

Enhancing multi-terminal network reliability with cost constraints using differential evolution and particle swarm optimization algorithms

Haider Saleh Howeidi
Department of Mathematics, College of Education for Pure Sciences, University of Babylon, Iraq.
Amir Sahib Mohammad Ali
Ministry of Education, Department of Mathematics, Babil Education Directorate, Babylon, Iraq.
Zahir Abdul Haddi Hassan
Department of Mathematics, College of Education for Pure Sciences, University of Babylon, Iraq.

Received: 06 Mar 2026 | Accepted: 07 May 2026 | Final Version: 30 May 2026

Abstract

In this study, we emphasize on reliability improvement of multi-terminal networks, that is, the complex of network nodes with inputs and outputs in flow of communication or energy with applications of the DE and PSO algorithms. The objective is to enhance the performance of the network within the bounds of a specified cost. The mutation, crossover, and selection based DE and the particle moving towards optimal solutions based PSO algorithms are modified to the unique needs of the multi-terminal network. These enhancements allow the algorithms to adapt component reliability effectively and therefore they address the dilemma of designing and operating such networks for reliability at an acceptable cost.

Keywords:
Multi-terminal networks, network reliability, differential evolution, particle swarm optimization, cost constraints.

1. Introduction

Multi-terminal networks are important infrastructures that support a wide range of applications, such as telecommunications, power delivery, and information management, and are composed of complex arrangements of linked nodes and elements. The reliability of such networks, as their capacity to fulfill required functions under defined conditions, should be guaranteed, which requires the development of super optimization tools that can combine the best solutions with the least cost. The present study is focused on analyzing the performance of optimization procedures, namely Differential Evolution and Particle Swarm Optimization, on reliability assessment of multi-terminal networks. The aim of this work is to adapt the above algorithms to complex network requirements in order to provide a methodology for network design and operation balancing reliability and cost, so as to inform the design of better and more sustainable systems.

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