Advanced Optimization Techniques for PASP: a Comparative Study of Improved PSO and BFO

EasyChair Preprint 13498

Abstract

In this study, we conduct a comparative analysis of advanced optimisation techniques: particle swarm optimization (PSO) and bacterial foraging optimization (BFO), applied to parallel assembly sequence planning (PASP) for a 10 MW wind turbine gearbox. The research focuses on optimising the assembly sequence to enhance efficiency, reduce costs, and improve the quality of the final product. We estimated a 10% improvement in assembly time using an enhanced PSO algorithm and a 15% improvement with BCF, alongside significant cost reductions and slight enhancements in quality. This comparative study elucidates the strengths and adaptability of both algorithms in handling complex optimization challenges within industrial applications. The results underscore the potential of these enhanced techniques to significantly impact the operational efficiency of large-scale manufacturing processes, particularly in the renewable energy sector. By systematically analysing the performance of improved PSO and BCF, this paper contributes valuable insights into optimising the assembly of intricate machinery, aiming for optimal resource utilisation and quality assurance in producing wind turbine gearboxes.

Keyphrases: Assembly sequence planning, Bacteria Foraging Optimization, Bacterial Foraging Optimization, Optimization Techniques, Parallel Assembly Lines, Parallel Assembly Sequence Planning, Particle Swarm Optimization PSO, Renewable Energy Sector, Wind turbine gearbox, assembly time hours, bacterial chemotaxis foraging bcf, best known position, efficiency improvement, elimination and dispersal, enhanced pso algorithm, improved bacterial foraging optimization, improved particle swarm optimization, improved pso and bcf, improvement with bcf, local search capabilities, mw wind turbine gearbox, objective function for pso, optimal resource utilisation and quality, optimization pso and bacterial, optimization pso and bacterial chemotaxis, precedence relationship and assembly time, pso and bacterial foraging, quality index, renewable energy and clean power, significant cost reductions, time and cost, total assembly time resulting, wind turbine gearboxes

@booklet{EasyChair:13498,
  author    = {Sydney Mutale and Yong Wang and Jan Yasir and Traore Aboubacar},
  title     = {Advanced Optimization Techniques for PASP: a Comparative Study of Improved PSO and BFO},
  howpublished = {EasyChair Preprint 13498},
  year      = {EasyChair, 2024}}