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This paper introduces a simultaneous optimization approach to synthesizing work and heat exchange networks (WHENs). The proposed work and heat integration (WHI) superstructure enables different thermodynamic paths of pressure and temperature-changing streams. The superstructure is connected to a heat exchanger network (HEN) superstructure, enabling the heat integration of hot and cold streams identified within the WHI superstructure. A two-step solution strategy is proposed, consisting of initialization and design steps. In the first step, a thermodynamic path model based on the WHI superstructure is combined with a model for simultaneous optimization and heat integration. This nonlinear programming (NLP) model aims to minimize operating expenditures and provide an initial solution for the second optimization step. In addition, hot and cold streams are identified, enabling additional model reduction. In the second step of the proposed solution approach, a thermodynamic path model is combined with the modified HEN model to minimize the network's total annualized cost (TAC). The proposed mixed integer nonlinear programming (MINLP) model is validated by several examples, exploring the impact of the equipment costing and annualization factor on the optimal network design. The results from these case studies clearly indicate that the new synthesis approach proposed in this paper produces solutions that are consistently similar to or better than the designs presented in the literature using other methodologies. [ABSTRACT FROM AUTHOR]

Microalgae have attracted great research interest as a feedstock for producing a wide range of end-products. However, recent studies show that the tight processing integration technology for microalgae-based biorefinery makes production less economical and even has a negative impact on sustainability. In this study, a new two-tier superstructure optimization design methodology is proposed to locate the optimal processing pathway. This model is developed based on the decomposition strategy and the relationship-based investigation, coupling an outer-tier structure with an inner-tier structure, wherein the outlet flows of the middle stages is relaxed and then an appropriate level of redundancy for designing the processing is provided. Two scenarios are developed to compare the most promising biorefinery configurations under two different design option favors. By solving the mixed integer nonlinear programming model with the objective functions of maximizing the yield of the desired products and maximizing the gross operating margin, the optimization results obtained show the ability of this framework to provide the promising configurations and cost-effectiveness of microalgae-based biorefinery. Compared with Scenario 1, the optimized solutions in Scenario 2 feature a gross operating margin increase up to 27.09% and an increase in product yield up to 25.00%. The proposed method improves the original huge computing scale and ensures economics without simplifying the processing pathways. [ABSTRACT FROM AUTHOR]

This work presents a superstructure optimization study for the production of renewable fuels with a focus on jet fuel. Power-to-X via the methanol (MTJ) and Fischer–Tropsch (FT) route is combined with Biomass-to-X (BtX) via an algae-based biorefinery to an integrated Power- and Biomass-to-X (PBtX) process. Possible integration by algae remnant utilization for H2/CO2 production, wastewater recycling and heat integration is included. Modeling is performed using the novel Open sUperstrucTure moDeling and OptimizatiOn fRamework (OUTDOOR). Novel methods to account for advanced mass balances and uncertain input data are included. Economic optimization proposes a PBtX process. This process combines algae processing with MTJ and depicts a highly mass- and energy integrated plant. It produces fuels at 211 EUR/MWhLHV (ca. 2530 EUR/t), a cost reduction of 21% to 11.5% compared to stand-alone electricity- or bio-based production at algae costs of 25 EUR/tAlgae-sludge and electricity costs of 72 EUR/MWh. Investigation of uncertain data indicates that a combination of BtX and MTJ is economically superior to FT for a wide parameter range. Only for high algae costs of >40 EUR/tAlgae-sludge stand-alone electricity-based MTJ is economically superior and for high MTJ costs above 2000–2400 EUR/tJet FT is the optimal option. [ABSTRACT FROM AUTHOR]

In Malaysia, palm oil industries have played significant roles in the economic sectors and the nation's developments. One aspect of these industries that is gaining growing interest is oil palm residue management and bio-based product generations. EFB has been identified to be a feasible raw material for the production of bio-energy, bio-chemicals, and bio-materials. In this paper, our previous deterministic mathematical programming model was extended to include decisions for selecting optimal transportation modes and processes at each level of the processing stage in the supply chain. The superstructure of alternatives was extended to show states of produced products whether solid, liquid, or gaseous, and for which truck, train, barge, or pipeline would be possible modes of transportation. The objective function was to maximize profit which accounts for associated costs including the emission treatment costs from production and transportation. The optimal profit was USD 1,561,106,613 per year for single ownership of all facilities in the supply chain. [ABSTRACT FROM AUTHOR]

Artificial Neural Networks (ANNs) have been used in a wide range of applications for complex datasets with their flexible mathematical architecture. The flexibility is favored by the introduction of a higher number of connections and variables, in general. However, over-parameterization of the ANN equations and the existence of redundant input variables usually result in poor test performance. This paper proposes a superstructure-based mixed-integer nonlinear programming method for optimal structural design including neuron number selection, pruning, and input selection for multilayer perceptron (MLP) ANNs. In addition, this method uses statistical measures such as the parameter covariance matrix in order to increase the test performance while permitting reduced training performance. The suggested approach was implemented on two public hyperspectral datasets (with 10% and 50% sampling ratios), namely Indian Pines and Pavia University, for the classification problem. The test results revealed promising performances compared to the standard fully connected neural networks in terms of the estimated overall and individual class accuracies. With the application of the proposed superstructural optimization, fully connected networks were pruned by over 60% in terms of the total number of connections, resulting in an increase of 4% for the 10% sampling ratio and a 1% decrease for the 50% sampling ratio. Moreover, over 20% of the spectral bands in the Indian Pines data and 30% in the Pavia University data were found statistically insignificant, and they were thus removed from the MLP networks. As a result, the proposed method was found effective in optimizing the architectural design with high generalization capabilities, particularly for fewer numbers of samples. The analysis of the eliminated spectral bands revealed that the proposed algorithm mostly removed the bands adjacent to the pre-eliminated noisy bands and highly correlated bands carrying similar information. [ABSTRACT FROM AUTHOR]

Industrial operations consume energy and water in large quantities without accounting for potential economic and environmental burdens on future generations. Consumption of energy (mainly in the form of high pressure steam) and water (in the form of process water and cooling water) are essential to all processes and are strongly correlated, which requires development of systematic methodologies to address their interconnectivity. To this end, the subject of heat-integrated water allocation network design has received considerable attention within the research community in recent decades while further growth is expected due to imposed national and global regulations within the context of sustainable development. The overall mathematical model of these networks has a mixed-integer nonlinear programming formulation. As discussed in this work, proposed models in the literature have two main difficulties dealing with heat–water specificities, which result in complex formulations. These difficulties are addressed in this work through proposition of a novel nonlinear hyperstructure and a sequential solution strategy. The solution strategy is to solve three sub-problems sequentially and iteratively generate a set of potential solutions through the implementation of integer cut constraints. The novel mathematical approach also lends itself to an additional innovation for proposing multiple solutions balancing various performance indicators. This is exemplified with both a literature test case and an industrial-scale problem. The proposed solutions address a variety of performance indicators which guides decision-makers toward selecting the most appropriate configuration(s) among a large number of potential possibilities. Results exhibit that despite having a sequential solution strategy, better performance can be reached compared to previous approaches with the additional benefit of providing many potential solutions for further consideration by decision-makers to select the best case-specific solution. [ABSTRACT FROM AUTHOR]

Genome-scale models have become indispensable tools for the study of cellular growth. These models have been progressively improving over the past two decades, enabling accurate predictions of metabolic fluxes and key phenotypes under a variety of growth conditions. In this work, an efficient computational method is proposed to incorporate genome-scale models into superstructure optimization settings, introducing them as viable growth models to simulate the cultivation section of biorefinaries. We perform techno-economic and life-cycle analyses of an algal biorefinery with five processing sections to determine optimal processing pathways and technologies. Formulation of this problem results in a mixed-integer nonlinear program, in which the net present value is maximized with respect to mass flowrates and design parameters. We use a genome-scale metabolic model of Chlamydomonas reinhardtii to predict growth rates in the cultivation section. We study algae cultivation in open ponds, in which exchange fluxes of biomass and carbon dioxide are directly determined by the metabolic model. This formulation enables the coupling of flowrates and design parameters, leading to more accurate cultivation productivity estimates with respect to substrate concentration and light intensity. [ABSTRACT FROM AUTHOR]

Industries consume large quantities of energy and water in their processes which are often considered to be peripheral to the process operation. Energy is used to heat or cool water for process use; additionally, water is frequently used in production support or utility networks as steam or cooling water. This enunciates the interconnectedness of water and energy and illustrates the necessity of their simultaneous treatment to improve energy and resource efficiency in industrial processes. Since the seminal work of Savulescu and Smith in 1998 introducing a graphical approach, many authors have contributed to this field by proposing graphically- or optimization-based methodologies. The latter encourages development of mathematical superstructures encompassing all possible interconnections. While a large body of research has focused on improving the superstructure development, solution strategies to tackle such optimization problems have also received significant attention. The goal of the current article is to study the proposed methodologies with special focus on mathematical approaches, their key features and solution strategies. Following the convention of Jeżowski, solution strategies are categorized into: decomposition, sequential, simultaneous, meta-heuristics and a more novel strategy of relaxation/transformation. A detailed, feature-based review of all the main contributions has also been provided in two tables. Several gaps have been highlighted as future research directions. [ABSTRACT FROM AUTHOR]