The Solution of a Multi-Objective Tool Selection Model Using the GA Approach

Tool switching problems in flexible manufacturing systems have been investigated over the last ten years. Work has also been carried out on minimising the number of tool switches and tool switching instances. Optimisation techniques are successful in locating optimum solutions. However, some solutions are slow in convergence and require time to attain the global minimum. Alternative methods which attempt to overcome this problem may risk being trapped at the local minima and fail to give the best solution. In this paper, a model was developed to minimise both the number of tool switches and tool switching instances simultaneously. Genetic algorithms (GAs) which have not been used to solve tool selection problems have been adopted to seek for the global optimum. GAs are found to be fast and efficient in locating an optimum or near optimum solution within an affordable time.