The scheduling problem of n printed circuit boards (PCBs) for m non-identical parallel machines is considered in this paper. The problem has to deal with three issues: (i) classifying the PCBs into m groups corresponding to m machines, (ii) sequencing the boards for each machine, and (iii) component switching (component unloading/loading) from the machine magazine. A general objective is to minimize the total makespan, which is shown here to be the same as minimizing the maximum number of component switches. The complete problem is complex, and is usually dealt with in stages, which may not yield a good solution. We model the problem in an integrated manner using weighted multiple objectives to deal with grouping of the boards, load balancing at each machine, board sequencing and component switching at a machine. A composite genetic algorithm is developed to solve this multi-objective problem. The integrated solution is encoded as a string of pair values for each group of boards. The first number indicates the board membership in a group, and the second one represents the sequencing position of a board in that group. A new population of solutions is generated by using both binary genetic operators for grouping and genetic operators for board sequencing. A fitness function evaluates workload balancing, board similarities and total setup time simultaneously. Experiments are designed and run to test the proposed methodology, and the results show that the solutions are efficient, and are obtained within a reasonable amount of time.
