Optimisation of process parameters using meta-heuristics algorithms for the manufacturing of leaf spring assembly

In solving the process optimisation problems, the classical optimisation methods are often encountered with great difficulties. Among the available optimisation procedures, the meta-heuristic techniques play a vital role for process optimisation when the search space is very wide. In this paper, the various process parameters used for the manufacture of leaf spring assembly are considered, analysed and optimised using a meta-heuristic optimisation procedure developed based on tabu search method (TSM) and simulated annealing (SA) algorithm. The adaptive memory structure and the four principle dimensions of TSM memory, such as recency, frequency, quality and influence, are effectively designed to suit to this problem environment. During the search process, the long-term memory and restarting criterion are found to strengthen the convergence capability of this algorithm. At the same time, the choice criterion along with the aspiration criterion is found to be very effective in diversifying the search process. The optimal schedule resulted out of this meta-heuristic algorithm is comparable with the solutions obtained by other different algorithms. And this developed procedure can be applied to any kind of related processes with small alterations.