This thesis aims to address the process synthesis problems of emerging reaction pathways for bio-based polymers and their monomers and provide the optimal design of the process flowsheet with simultaneous heat integration. To solve these problems, mixed integer linear programming (MILP) models and solution approaches are developed along with a decomposition method to handle numerical complications arising from the utilisation of a large number of discretised variables.
Regarding the process synthesis problem, an optimisation-based framework is first developed to identify the optimal configuration of a process network that consists of both reaction and separation systems. The problem is formulated as a mixed integer linear programming (MILP) model with the objective to maximise the economic potential. A logic-based formulation using binary variables is designed for the simultaneous synthesis of separation sequences. The solution of the optimisation problem includes the best possible economic performance, identification of active reactions, reaction ordering and separation sequences along with the corresponding flowsheet of the entire process. Secondly, simultaneous heat integration is incorporated into the model without introducing nonlinearity by using a novel variable discretisation approach. The modified model aims to provide additional information of the optimal flowsheet such as the utility cost, the minimum cooling and heating duties required, and energy savings due to heat integration.
The process synthesis model consists of a large number of integer variables and becomes difficult to solve. A decomposition method, which utilises the GAMS grid facility, breaks down the original problem into an equivalent set of subproblems by the partitioning of decision variable domains and allows inter-job communications to exchange the best bound of each subproblem. The results indicate that significant improvement in the computational efficiency is achieved when inter-job communication is integrated with the decomposition method.