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              <p>&lt;p&gt;Scheduling decisions in the diffusion area of a semiconductor manufacturing facility&lt;br /&gt;have an important impact on the overall performance of a plant. Consequently, we want&lt;br /&gt;to optimize those decisions while taking real-world constraints into account. The problem&lt;br /&gt;we address is a generalization of a job shop with multiple resources per operation. We&lt;br /&gt;aim to optimize several objectives that comprise throughput and waiting time.&lt;/p&gt; &lt;p&gt;&lt;br /&gt;The operations to be performed in the diffusion area are cleaning or furnace operations&lt;br /&gt;that need specific machines. To obtain practicable schedules, we consider complex&lt;br /&gt;machines of that area in detail and include their components as resources in our model.&lt;br /&gt;Complex machines consist of tubes, boats and a load port. A tube is the place where&lt;br /&gt;processes are conducted. A boat is a moveable carrier for wafers needed for all operations&lt;br /&gt;in a machine. The load port is the place where wafers are loaded and unloaded.&lt;br /&gt;For those resources, we are given synchronization constraints that can be explained using&lt;br /&gt;two characteristic examples: Firstly, if a loading operation uses the load port of&lt;br /&gt;a machine, the corresponding unloading operation must use the load port of the same&lt;br /&gt;machine. Secondly, after a specific boat is loaded, it cannot be used elsewhere before&lt;br /&gt;being unloaded. So, a resource can be blocked even if no operation is currently using it.&lt;/p&gt; &lt;p&gt;&lt;br /&gt;Many approaches from literature extend the job shop problem to the needs of realworld&lt;br /&gt;problems. However, we are not aware of any work that addresses resource dependencies&lt;br /&gt;as described above. For the given problem, we present a construction algorithm&lt;br /&gt;to find an initial solution. We propose a suitable disjunctive graph representation that&lt;br /&gt;adapts ideas from Dauzère-Pérès and Paulli (1997) and introduce moves that form a&lt;br /&gt;basis for different metaheuristics. Finally, we present results of an implementation.&lt;/p&gt;</p>
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