Solution approaches for a real-life resource-constrained parallel machine scheduling problem

This paper deals with a real-world scheduling problem in an injection-molding department of an electrical appliance plant. In the department, a resource-constrained parallel machine scheduling problem with machine eligibility restrictions is investigated. First, an integer-programming (IP) model with the objective of minimizing makespan is developed for the entire problem. Since this entire IP model has a huge number of variables, it cannot handle the problem efficiently. To obtain more efficient results, two solution approaches, namely IP/IP and IP/constraint programming (CP) both of which partition the entire problem into loading and scheduling sub-problems, are proposed. The loading phase, in which an IP loading model assigns the jobs to machines with the aim of minimizing maximum load on the machines and operators, is the same for both approaches. Subsequently, in the scheduling phase, the IP/IP approach uses an IP scheduling model while the IP/CP approach applies a CP scheduling model to obtain the final schedule of the jobs. Computational results show that the proposed solution methods improve makespan values for almost all test problems in comparison to the entire IP model. In particular, the IP/IP approach performs better in the test problems with greater number of operators, whereas IP/CP approach provides quick and practical results in almost all test problems and gives relatively more efficient makespan values when the resource constraints are tight (i.e., the case of smaller number of operators).