Supply chains are complex industrial systems with several actors that strive towards different purposes. These systems are particularly sensitive to dynamic complexity and are popularly approached using system dynamics simulation. A common problem with system dynamics simulation is the inability to see directly how well a model with several objectives performs.
This article suggests multi-objective optimisation as a means of analyzing dynamic supply chain models to (1) find Pareto-optimal parameter sets and (2) allow for comparison of different models by comparing Pareto fronts. Apart from discussing the application of multiobjective optimisation to dynamic supply chain problems, a supply chain model is optimized to give some insight about the benefits of using multi-objective optimisation for supply chain problems.
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