Selection of wire electrical discharge machining process parameters using non-traditional optimization algorithms

Authors:
Rajarshi Mukherjee;Shankar Chakraborty;Suman Samanta
Affiliations:
Department of Production Engineering, Jadavpur University, Kolkata 700032, West Bengal, India;Department of Production Engineering, Jadavpur University, Kolkata 700032, West Bengal, India;Department of Production Engineering, Jadavpur University, Kolkata 700032, West Bengal, India
Venue:
Applied Soft Computing
Year:
2012

Citing 11
Cited 0

An ant algorithm for optimization of hole-making operations

Computers and Industrial Engineering
Facing classification problems with Particle Swarm Optimization

Applied Soft Computing
On the performance of artificial bee colony (ABC) algorithm

Applied Soft Computing
Particle swarm optimization technique based short-term hydrothermal scheduling

Applied Soft Computing
Parameter optimization of a multi-pass milling process using non-traditional optimization algorithms

Applied Soft Computing
Optimization of wire electrical discharge machining for pure tungsten using a neural network integrated simulated annealing approach

Expert Systems with Applications: An International Journal
Ant Colony Optimization based approach for efficient packet filtering in firewall

Applied Soft Computing
An improved evolutionary method with fuzzy logic for combining Particle Swarm Optimization and Genetic Algorithms

Applied Soft Computing
Analytical and numerical comparisons of biogeography-based optimization and genetic algorithms

Information Sciences: an International Journal
An ant colony optimization algorithm for setup coordination in a two-stage production system

Applied Soft Computing
Biogeography-Based Optimization

IEEE Transactions on Evolutionary Computation

Quantified Score

Hi-index	0.00

Visualization

Abstract

Selection of the optimal values of different process parameters, such as pulse duration, pulse frequency, duty factor, peak current, dielectric flow rate, wire speed, wire tension, effective wire offset of wire electrical discharge machining (WEDM) process is of utmost importance for enhanced process performance. The major performance measures of WEDM process generally include material removal rate, cutting width (kerf), surface roughness and dimensional shift. Although different mathematical techniques, like artificial neural network, gray relational analysis, simulated annealing, desirability function, Pareto optimality approach, etc. have already been applied for searching out the optimal parametric combinations of WEDM processes, but in most of the cases, sub-optimal or near-optimal solutions have been arrived at. In this paper, an attempt is made to apply six most popular population-based non-traditional optimization algorithms, i.e. genetic algorithm, particle swarm optimization, sheep flock algorithm, ant colony optimization, artificial bee colony and biogeography-based optimization for single and multi-objective optimization of two WEDM processes. The performance of these algorithms is also compared and it is observed that biogeography-based optimization algorithm outperforms the others.