Many-Objective Optimization of Distributed Heterogeneous Hybrid Flowshop Lot-Streaming Scheduling Problem with Missing Operations

The distributed heterogeneous hybrid flowshop lot-streaming scheduling problem with missing operations (DHHFLSPMO), a common occurrence in manufacturing sectors like stainless steel factory and steel furniture manufacturing factory, has not been widely investigated. In this paper, a many-objective evolutionary algorithm based on multiple populations collaborative search (MaEA/MPCS) is proposed to solve the DHHFLSPMO with the criteria of minimizing makespan, total flow time, total weighted earliness and tardiness, and idle time of machines. First, four populations are utilized to optimize the four objectives individually. Second, one population interacts with another to avoid overly focusing on one objective during the course of evolution. Third, an archive is established to collect all the nondominated solutions, and is updated using fast nondominate sorting method and crowding distance. Finally, the computational simulation is conducted, and the results demonstrate that the proposed MaEA/MPCS surpasses its competitors by a significant margin.