A major advantage of Flexible Manufacturing Systems (FMS) is that a family of related parts can be processed simultaneously using sets of computer controlled workstations, capable of performing a number of different operations and interconnected by automated material handling devices. Flexible manufacturing industry is marked by the coexistence of several resources with varying capabilities, capacities and functions. In such systems the selection of appropriate resources (e.g. tool selection, tool management or tool loading) for machines and allocation of appropriate resources to them is one of the major decision problems is generally handled by two approaches i.e. by minimizing the total manufacturing cost or by minimizing the total manufacturing time. Both these approaches lead to NP-hard problems and thus need the application of heuristic techniques or AI based optimization tools to achieve an optimal or near optimal solution. In this chapter, a hybrid algorithm named Simulated Annealing-Tabu is utilized to solve this computationally complex problem. This hybrid algorithm exploits the features of tabu search and simulated annealing to ensure convergence at a faster rate.
|Title of host publication
|Evolutionary Computing in Advanced Manufacturing
|Manoj Tiwari, Jenny A. Harding
|Number of pages
|Published - 20 Jun 2011