Separation of mixtures chemicals, ubiquitous in chemical and petrochemical industries, by distillation is energy intensive. Nearly 3% the overall used for United States. Improving process crucial making industries more sustainable. However, designing sequences challenging because choice set vast, equations governing physical are highly nonconvex. Traditional design practices rely on heuristics ...

This paper proposes optimal operational planning for cogeneration system (CGS) using particle swarm optimization (PSO). CGS is usually connected to various facilities such as refrigerators, reservoirs, and cooling towers. In order to generate optimal operational planning for CGS, startup/shutdown status and/or input/output values of the facilities for each control interval should be determined....

An optimal design strategy for membrane networks separating multicomponent gas mixtures based on an approximate permeator model and mixed-integer nonlinear programming (MINLP) is proposed. A permeator system superstructure is used to embed a very large number of possible network configurations and allows the permeator feed-side pressure to be fixed or a design variable. A MINLP design model is ...

For the separation of azeotropic mixtures with distillation usually a number of conceptual design alternatives are generated. Instead of evaluating the economic viability of the different alternatives by repetitive simulation studies, a combination of shortcut calculations and rigorous MINLP optimization is proposed. In this two step process the shortcut calculations are used to screen and rank...

In this paper, we introduce a generalized multiperiod scheduling version of the pooling problem to represent time varying blending systems. A general nonconvex MINLP formulation of the problem is presented. The primary difficulties in solving this optimization problem are the presence of bilinear terms, as well as binary decision variables required to impose operationalconstraints . An illustra...

The long-term planning of the shale gas supply chain is a relevant problem that has not been addressed before in the literature. This paper presents a mixed-integer nonlinear programming (MINLP) model to optimally determine the number of wells to drill at every location, the size of gas processing plants, the section and length of pipelines for gathering raw gas and delivering processed gas and...

In this study, a flexible optimization approach is introduced to design an optimal biocompatible solvent for an extractive fermentation process with cell-recycling. The optimal process/solvent design problem is formulated as a mixed-integer nonlinear programming model in which performance requirements of the compounds are reflected in the objectives and the constraints. A flexible or fuzzy opti...

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),...

Decentralized energy supply systems (DESS) are highly integrated and complex systems designed to meet time-varying energy demands, e.g., heating, cooling, and electricity. The synthesis problem of DESS addresses combining various types of energy conversion units, choosing their sizing and operations to maximize an objective function, e.g., the net present value. In practice, investment costs an...

We address the optimal dynamic formation problem in mobile leader-follower networks where an optimal formation is generated to maximize a given objective function while continuously preserving connectivity. We show that in a convex mission space, the connectivity constraints can be satisfied by any feasible solution to a mixed integer nonlinear optimization problem (MINLP). For the class of opt...