AbstractWelding is a well-known process in manufacturing industries due to its importance. Several process parameters should be tuned in order to perform a high-quality welding. Usually, the problem is described as an optimization one and the challenge is to reconcile conflicting objectives. This paper deals with a multi-objective welding process namely the submerged arc welding process, involving five objectives. The weighted sum approach is used to handle it. An accelerated cuckoo optimization algorithm is implemented for this process model and applied to a practical instance of it. On this practical example, the superiority of the proposed optimization technique has been demonstrated in terms of better solutions and fewer required generations of the cuckoos relative to the basic COA and four other optimization algorithms.
Filter-Based Multi-Objective Feature Selection Using NSGA III and Cuckoo Optimization Algorithm
