GAUSSIAN TRANSFER FUNCTIONS BASED BINARY PARTICLE SWARM OPTIMIZATION FOR ENHANCED PERFORMANCE IN UN-CAPACITATED FACILITY LOCATION PROBLEM

  • 1Department of Mechanical Engineering, Vel Tech Rangarajan Dr, Sagunthala R&D Institute of Science and Technology, Avadi, IN
  • 2Department of Machining, Assembly and Engineering Metrology, Faculty of Mechanical Engineering, VSB-Technical University of Ostrava , Ostrava, CZ
  • 3Department of Biosciences, Saveetha School of Engineering. Saveetha Institute of Medical and Technical Sciences, Chennai, IN

Abstract

This study introduces Gaussian Binary Particle Swarm Optimization (G-BPSO), designed to address binary optimization challenges effectively. G-BPSO employs new transfer functions of the Gaussian type derived from the power functions to enable mapping of real-valued vectors of individual encodings into binary form. This ensures smooth change between steps and improved convergence. To assess the effectiveness of G-BPSO, a host of complex optimization problems such as the un-capacitated facility location problem are investigated. Enhanced efficiency and improvement over existing methods in binary optimization is observed. The MATLAB code of G-BPSO is made open-access through https://github.com/kanak02/GBPSO.

Recommended articles

THE INFLUENCE OF QUENCHING AND TEMPERING ON THE HARDNESS AND MICROSTRUCTURE OF 42CrMo4 STEEL

A. Milinovic, J. Mijic, S. Simunovic, I. Kladaric
Keywords: Quenching and Tempering | 42CrMo4 Steel | Hardness | Microstructure