AN ADAPTABLE PROBLEM-SPACE-BASED SEARCH METHOD FOR FLEXIBLE FLOW LINESCHEDULING

Problem-space-based neighborhoods have been recently suggested in the literature for the approximate solution of scheduling problems. This p aper explores how effectively these neighborhoods can be adapted to di fferent regular measures of performance in the context of flexible flo w line scheduling. Specifically, makespan and mean tardiness are used in the experiments. Near-optimal solutions and significant improvement s in the performance of single-pass heuristics are found when searchin g these spaces with simple local search techniques for industrial and randomly generated problems.