John W. Fowler

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Even though we have moved beyond the Industrial Age and into the Information Age, manufacturing remains an important part of the global economy. There have been numerous efforts to use modeling and simulation tools and techniques to improve manufacturing efficiency over the last four decades. While much progress has been made and an increasing number of(More)
This research is motivated by a scheduling problem found in the di6usion and oxidation areas of semiconductor wafer fabrication, where the machines can be modeled as parallel batch processors. We attempt to minimize total weighted tardiness on parallel batch machines with incompatible job families and unequal ready times of the jobs. Given that the problem(More)
The di0usion step in semiconductor wafer fabrication is very time consuming, compared to other steps in the process, and performance in this area has a signi1cant impact on overall factory performance. Di0usion furnaces are able to process multiple lots of similar wafers at a time, and are therefore appropriately modeled as batch processing machines with(More)
In this paper, the computational performance of four different mixed integer programming (MIP) formulations for various single machine scheduling problems is studied. Based on the computational results, we discuss which MIP formulation might work best for these problems. The results also reveal that for certain problems a less frequently used MIP(More)
In this paper we propose a two-stage Multi-Population Genetic Algorithm (MPGA) to solve parallel machine scheduling problems with multiple objectives. In the first stage, multiple objectives are combined via the multiplication of the relative measure of each objective. Solutions of the first stage are arranged into several sub-populations, which become the(More)