Decomposition-based scheduling algorithm for large-scale job shop

Abstract

A multi-bottleneck scheduling algorithm based on rolling horizon decomposition is proposed for large-scale job shop scheduling problems, in which the total weighted tardiness must be minimized. The algorithm divides the original problem into a number of subproblems according to the process route of each job, and gets the solution of the original problem by constructing and solving the subproblems iteratively. A multi-bottleneck detection method based on critical path method is proposed to detect the bottlenecks in the problem. According to the principle of "bottleneck machines lead non-bottleneck machines" in TOC, the operations processed on bottleneck machines are scheduled by genetic algorithm, and the operations processed on non-bottleneck machines are scheduled by dispatching rules to improve the computing efficiency. Simulation results show that the algorithm is effective for large-scale job shop scheduling problems.