Self-Optimization module for Scheduling using Case-based Reasoning
Applied Soft Computing
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Production scheduling in multiple-stage multiple- machine multiple-product environment is a NP hard problem usually faced by make/engineer-to-order companies engaged in capital goods Industry. Feasible schedules must correctly sequence the operations required to manufacture components and also satisfy assembly precedence relationships. This paper presents the development of Artificial Bee Colony algorithm for solving the scheduling problem. Based on Just in time philosophy, the proposed algorithm was designed to minimise the combination of earliness and tardiness penalties cost. The computational experiment was conducted using data obtained from a collaborating company that manufactures complex capital goods. The aim was to investigate the influence of parameter configuration on the algorithm performance. The analysis of variance on the experimental results indicated that the performance can be improved dramatically after adopting the optimum parameter setting.