On the configuration of supply chains for assemble-to-order products: Case studies from the automotive and the CNC machine building sectors

The product customisation trend has an unprecedented impact on manufacturing companies, as the ever-increasing number of product variants and the enlarged pool of cooperating partners vastly increase the feasible alternative supply chain configurations. In terms of decision theory, this is translated to enormous search spaces. For tackling these NP-hard problems, metaheuristic optimisation methods are utilised, which provide a trade-off between the quality of solutions and the computation time. This research work describes the modelling and solving of two supply chain configuration problems using the Simulated Annealing and Tabu Search methods. The performance of the identified solutions in terms of optimisation of multiple conflicting criteria, is compared against the results obtained from a custom Intelligent Search Algorithm and an Exhaustive enumerative method. The algorithms are developed into a web-based software platform. The approach is validated through real life applications to case studies from the automotive and CNC laser welding machine building industries.