particle swarm optimization

Using the Mountain Gazelle Optimizer to Construct Consistent Pairwise Comparison Matrices Within Acceptable Consistency Ratio Thresholds

The Analytic Hierarchy Process (AHP) fundamentally relies on the pairwise comparison matrix (PCM) as a core component in structuring multi-criteria decision-making problems, with applications spanning numerous disciplines.  This paper introduces a novel methodology for generating consistent PCMs that satisfy a predefined threshold for the consistency ratio (CR).  The proposed approach leverages the Mountain Gazelle Optimizer (MGO), a recent metaheuristic algorithm inspired by the social hierarchy and herd behavior of wild mountain gazelles.  Numerical experiments demons

Physics-Informed Particle Swarm Optimization for Collision-Aware Swarm Navigation

This paper presents an approach to modeling the movement of a multi-agent system in a two-dimensional space using a modified Particle Swarm Optimization (PSO) algorithm, adapted to account for the physical properties of the agents. The standard PSO, originally designed for solving optimization problems through swarm behavior, has been extended to simulate the motion of physical objects with defined mass, velocity, and inter-agent interactions.

PSOBER: PSO based entity resolution

Entity Resolution  is the task of mapping the records within a database to their corresponding entities.  The entity resolution problem presents a lot of challenges because of the absence of complete information in records, variant distribution of records for different entities and sometimes overlaps between records of different entities.  In this paper, we have proposed an unsupervised method to solve this problem.  The previously mentioned problem is set as a partitioning problem.  Thereafter, an optimization algorithm-based technique is proposed to solve the entity resolution problem.  T

Analysis and Optimization of the Sizes of the Iteration Space Tiles During the Parallelization of Program Loop Operators

The analysis of the dependency of influence of the tile sizes of iteration space has been represented. It involves program loop operators’ modification during parallelization for multithreading architectures of the computation systems. The particle swarm optimization method has been considered as a method of the minimization program execution time for tiling speed up.