This paper first describes an empirical model to characterize the deactivation of a catalyst used in the production of a specialty chemical based on actual plant data. This model is then used in a novel multiperiod MINLP optimization formulation that incorporates the empirical model in order to determine the optimal catalyst replacement policy and meet time varying product demand.

In this paper a discrete location model for non-essential service facilities planning is described, which seeks the number, location, and size of facilities, that maximizes the total expected demand attracted by the facilities. It is assumed that the demand for service is sensitive to the distance from facilities and to their size. It is also assumed that facilities must satisfy a threshold lev...

Recently, the so-called ψ-learning approach, the Support Vector Machine (SVM) classifier obtained with the ramp loss, has attracted attention from the computational point of view. A Mixed Integer Nonlinear Programming (MINLP) formulation has been proposed for ψ-learning, but solving this MINLP formulation to optimality is only possible for datasets of small size. For datasets of more realistic ...

Global optimization for sustainable design and synthesis of a large-scale algae processing network under economic and environmental criteria is addressed. An algae processing network superstructure including 7800 processing routes is proposed. Based on the superstructure, a multiobjective mixed-integer nonlinear programming (MINLP) model is developed to simultaneously optimize the unit cost and...

This paper studies the multi-stage supply chain system (MSSCM) controlled by the kanban mechanism. In the kanban system, decision making is based on the number of kanbans as well as batch sizes. A kanban mechanism is employed to assist in linking different production processes in a supply chain system in order to implement the scope of just-in-time (JIT) philosophy. For a MSSCM, a mixed-integer...

This paper proposes a multiobjective, mixed-integer nonlinear programming (MINLP) model for the superstructure optimization of hydrocarbon biorefineries via gasification pathway under economic and environmental criteria. The proposed hydrocarbon biorefinery superstructure includes a number of major processing stages, such as drying of the cellulosic biomass feedstocks, air separation unit, gasi...

In this work, we address the rigorous and efficient determination of the global solution of a nonconvex MINLP problem arising from product portfolio optimization introduced by Kallrath (2003). The goal of the optimization problem is to determine the optimal number and capacity of reactors satisfying the demand and leading to a minimal total cost. Based on the model developed by Kallrath (2003),...

The rigorous and efficient determination of the global solution of a nonconvex MINLP problem arising from product portfolio optimization introduced by Kallrath (2003) is addressed. The objective of the optimization problem is to determine the optimal number and capacity of reactors satisfying the demand and leading to a minimal total cost. Based on the model developed by Kallrath (2003), an imp...

The analytical target cascading (ATC) methodology for optimizing hierarchical systems has demonstrated convergence properties for continuous, convex formulations. However, many practical problems involve both continuous and discrete design variables, resulting in mixed integer nonlinear programming (MINLP) formulations. While current ATC methods have been used to solve such MINLP formulations i...