Abstract

This article studies the speed-scaling robotic cell scheduling problem with constrained peak power consumption. The objective is to minimize cycle time and peak power consumption simultaneously. First, we formulate a bi-objective mixed integer programming model for the problem and propose a strategy to preprocess overlapping time windows. Then, we analyze the structural properties of the proposed model and develop an iterative $ \varepsilon $-constraint method to generate its complete Pareto front. Numerical experiments demonstrate that the proposed method effectively solves the robotic cell scheduling problem and that appropriate scheduling of speed-scaling machines can make a trade-off between productivity and power consumption.

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