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PhD - Optimisation of batch plant design: mathematical models and algorithms for strategic decision support
Chemical batch plants provide us with a variety of products, such as pharmaceuticals, food additives and lubricants. The construction of such batch plants comes with significant investments, which gives rise to the strategic batch plant design problem. This problem entails determining the optimal number and size of equipment units for every production stage, as well as the optimal operational planning guidelines. The aim is to minimise total costs while satisfying both demand and design related constraints. These demand and design constraints generally state that the designed plant should be large enough to produce a given, total demand for a range of products within a given production horizon.
The batch plant design problem has been studied extensively in literature over the past decades and is usually formulated as a mixed-integer linear programming problem that is solved exactly. There is, however, still a need for bringing the existing models and solution techniques a step closer to reality. With this goal in mind, a first contribution of the dissertation relates to the modelling of real-life chemical batch plants. Such plants typically consist of parallel production lines, i.e. lines that can be dedicated to particular products or product families, which we included as a design option into existing plant design models found in literature. Secondly, we investigated the operational use, i.e. how the plant is used, for the plant design problem with parallel production lines. Next to a single product campaign mode of operation, two additional, more complex, modes were examined: mixed-product campaigns and network planning. As a third contribution, different solution techniques, such as a matheuristic optimisation algorithm, were developed to solve these design problems within limited computation time. Finally, we considered the multiperiod version of the batch plant design problem and proposed an appropriate delivery framework. This framework allows to systematically combine different delivery and production planning characteristics that arise in such a multiperiod context. We performed an exploratory study to investigate the impact of this multiperiod delivery framework on the plant design, and this for both a plant operating in a single and a mixed-product campaign mode.
List of publications
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List of presentations
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