Presentation 8: Improved Particle Swarm Optimization for Non-linear Programming Problem
Channel: Editor GIAP Journals
Date: 16/11/2016

Author's: Raju Prajapati, Department of Mathematics, University of Engineering and Management University, Kolkata, West Bengal 700156 (India). 
Dr.Om Prakash Dubey, Department of Mathematics, Bengal College of Engineering and Technology, Durgapur, West Bengal-713212 (India).
 Randhir Kumar, Department of Mechanical Engineering, Bengal College of Engineering and Technology, Durgapur, West Bengal-713212 (India).
Email: raju.prajapati20102011@gmail.com
The Non-Linear Programming Problems (NLPP) are computationally hard to solve as compared to the Linear Programming Problems (LPP). To solve NLPP, the available methods are Lagrangian Multipliers, Sub gradient method, Karush-Kuhn-Tucker conditions, Penalty and Barrier method etc. In this paper, we are applying Barrier method to convert the NLPP with equality constraint to an NLPP without constraint. We use the improved version of famous Particle Swarm Optimization (PSO) method to obtain the solution of NLPP without constraint. SCILAB programming language is used to evaluate the solution on sample problems. The results of sample problems are compared on Improved PSO and general PSO.