Constraint Programming for a Novel Integrated Optimization of Blocking Job Shop Scheduling and Variable-Speed Transfer Robot Assignment

Abstract

Blocking job shop scheduling problems are common in industrial environments. Various existing studies tackle them to enhance the production efficiency of job shops with machine blocking properties. In the environment of intelligent manufacturing, robots are commonly used to transfer the jobs to be processed among different processes. However, no previous work considers the integrated optimization of blocking job shop scheduling and transfer robot assignment. Facing the new and key demand of production scheduling, this work considers a novel blocking job shop scheduling problem with transfer robots whose speed varies with or without cargo load. It is first formulated by using constraint programming as a baseline model. By analyzing the characteristics of both the considered problem and baseline model this work proposes an improved constraint programming model. Numerous experiments on an adapted benchmark dataset show that the improved constraint programming model can well solve the concerned problem. Comparing with a baseline model, it can greatly enhance the solution efficiency and accuracy. Its great performance shows its high potential to be used in practical industrial scenarios.