To build a generator-manufacturing plant can cost several hundred million US dollars. This study proposes an integrated model combining a set of non-linear mixed integer programming and simulation models both to solve the decision-making problem regarding the design of a generator-manufacturing plant and simultaneously to optimise the plant's capacity, facility layout, and production planning. The model proposed here consists of three interrelated stages. The first stage determines, by an integer programming model, the least number of machines to be invested that fulfils all the committed demands with a minimal cost. This tentative capacity configuration of manufacturing resources is then tuned through a simulation evaluation. On the basis of the resulting capacity configuration determined, in the second stage, we propose a 0-1 mixed-integer programming model for facility layout to minimise the total transportation cost. In the third stage, we construct a 0-1 mixed-integer programming model for task scheduling to determine the best production plan in terms of makespan minimisation, given the best capacity configuration and facility layout as determined in the first two stages. Case-study experiments have shown that the proposed integrated model can achieve a good facility design for building a generator plant and can significantly reduce the plant's installation and operational costs.
