An evolutionary simulation-based optimization approach for dispatching scheduling

An effective scheduling decision is one of the key factors towards improving the efficiency of a system’s performance, particularly in the instance of multiple products thus dispatching rules have been widely used for real-time scheduling because they can provide a very quick and pretty good solution. However, deciding how to select appropriate rules is very difficult. In this paper, we develop evolutionary simulation-based heuristics to construct near-optimal solutions for dispatching rule allocation. Our heuristic is easy to use and gives a manager a useful tool for testing a configuration that can minimize certain performance measures. The optimization heuristics are used to determine priority strategies to maximize the performance of a complex manufacturing system with a large number of different products, along with an overtime that changes with a mix of different process types, including assembly and disassembly operations and with different types of internal and external disturbances. Modeling is carried out using discrete-event simulation. Case study analysis is of a commercial offset printing production system.