Abstract

The previous studies on scheduling problem with tool changes take processing time as the only reason for the tool wear, which is not accurate in the real manufacturing system. This paper takes processing speed and processing time into consideration simultaneously and proposes a new unrelated parallel machine scheduling problem (UPMSP) with tool changes caused by the tool wear, in which the energy consumption rate of the parallel machines is influenced by two factors: tool changes and corresponding processing speed. A new effective heuristic evolutionary algorithm (NHEA) is presented to solve the proposed UPMSP with objectives of optimising total energy consumption and makespan. For the NHEA, some effective operators such as target-searching operators are designed to accelerate the search efficiency and further exploit the solution space. A first fit decreasing algorithm is presented and incorporated into the NHEA to reduce the number of tool changes. The Taguchi method of Design of Experiments is used to obtain the best combination of key parameters of the NHEA. Extensive computational experiments are carried out to compare the NHEA with some well-known algorithms. The results validate that the proposed NHEA is able to obtain better Pareto solutions for UPMSP with tool changes.

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