Abstract
This article studies a steelmaking-continuous casting (SCC) scheduling problem by considering ladle allocation. It takes technological rules in steel manufacturing and ladle-related constraints into account. A scheduling problem is formulated to determine allocation equipment for jobs, production sequence for jobs processed by the same equipment, and modification operations for empty ladles after their service for jobs. To ensure the fastest production and least energy consumption, we present a mixed integer mathematical programming model with the objectives to minimize the maximum completion time, idle time penalties, and energy consumption penalties related to waiting time. To solve it, we develop a two-stage approach based on a combination of scatter search (SS) and mixed integer programming (MIP). The first stage applies an SS algorithm to determine the assignment and sequence variables for charges. For the obtained solution, we construct a temporal constraint network and establish an MIP model at the second stage. We apply ILOG.CPLEX to solve the model and find the final solution. We analyze and compare the performance of the proposed approach with a hybrid method that combines a genetic algorithm with MIP on instances constructed from a real iron-steel plant. To further verify the effectiveness of the proposed algorithm, we compare its results with optimal solutions of the constraint-relaxed original problem. The experimental results show the effectiveness of the proposed approach in solving the SCC-scheduling problem. Note to Practitioners-This article deals with a scheduling problem arising from a steelmaking-continuous casting process in steel manufacturing. It integrates ladles allocation into the scheduling problem to reduce the energy consumption as much as possible. Such a problem in the existing work is handled, respectively, and its solutions tend to cause much energy waste and some mismatched plans. This article takes complex technological constraints into full account and minimizes the maximum job completion time, idle time of equipment, and waiting time of jobs. It establishes a mixed integer mathematical model and proposes a hybrid algorithm that combines scatter search and mixed integer programming to solve it. The extensive results demonstrate that the proposed approach can effectively solve the studied scheduling problem. The obtained solution gives decision makers some desired reference to determine a right schedule when an actual production process is conducted.