Abstract
With the sharply increasing energy demand and the shortage of energy, the scheduling goal of hot rolling production (HRP) is to select and sequence slabs to reduce cost and energy consumption. A multi-objective HRP optimal scheduling model is formulated and transferred as a multi-objective prize collecting vehicle routing problem (MO-PCVRP) with special constraints that simultaneously minimizes the jump cost of width, thickness, and hardness between adjacent slabs, the total length of unselected slabs, and the energy cost. Furthermore, this paper introduces a greedy strategy to intensify the local search of the standard NSGA-II algorithm, and names it local-intensification NSGA-II (LI-NSGA-II). The comparison experiments show that the LI-NSGA-II algorithm obtains better comprehensive performance than other compared algorithms in solving multi-objective scheduling problems of HRP.
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