Mixed integer optimization methods for synthesis, design and scheduling of batch chemical processes

This dissertation deals initially with a special class of nonlinear discrete optimization problems for the optimal design of systems with discrete sizes. It is assumed that the model involves nonlinear separable objective functions and bilinear constraints. These constraints involve products of design and state variables in which the former are restricted to take discrete values. Two special cases are identified for which advantage can be taken of the discrete nature of the design variables to reformulate these problems as MILP models which can be solved to global optimality. The application of the MILP reformulations is applied to multiproduct batch plant problems in chemical engineering and to structural design problems in civil engineering.; Next, the objective is to show that many nonlinear models for batch design, which are based on the assumption of continuous sizes, can be reformulated as MILP problems when sizes are restricted to discrete values. Problems considered include multiproduct plants operating with single product and mixed product campaigns, and multipurpose plants with single and multiple production routes.; We then address the problem of determining the optimal configuration and cyclic operation of batch plants in which all the products require the same processing sequence. In particular, the problem consists in determining the following items: number, type and size of equipment, as well as their allocation to one or multiple tasks and possible parallel operation: location and size of intermediate storage vessels; the length of the production cycle including the sequence of production of the products; levels of product inventories. The objective is to maximize the net present value.; Finally, we propose a unified method for addressing the problem of integrated scheduling and design for a special class of multipurpose batch processes. The type of plants considered are the ones where not all the products use the same processing stages, and manufacturing of the products can be characterized through production routes. A novel representation for cyclic schedules is proposed that has the effect of aggregating the number of batches for each product. It is shown that the no-wait characteristics of subtrains can be exploited with a reduction scheme that has the effect of greatly reducing the dimensionality of the problem. By using exact linearization schemes it is shown that the problem can be reformulated as an MILP model and solved rigorously to global optimality. (Abstract shortened by UMI.)...