MILP-based decomposition algorithm for dimensionality reduction in multi-objective optimization: Application to environmental and systems biology problems

Copado-Méndez, Pedro J.; Guillén‐Gosálbez, Gonzalo; Jiménez, Laureano

doi:10.1016/j.compchemeng.2014.04.003

Cited by 21 publications

(9 citation statements)

References 24 publications

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“…Note that model RSUMOD makes use of both, the surrogate model SURMOD obtained in step In order to solve problem RSUMOD and obtain a set ot Pareto optimal solutions, one can use any MOO method available in the literature [46][47][48][49]. Without loss of generality, here we use the epsilon constraint method [50,51], which consists of calculating a set of auxiliary singleobjective problems in which one objective is kept as main criterion while the others are transferred to auxiliary constraints and limited within allowable bounds.…”

Section: Moo Of the Surrogate Model In The Reduced Domainmentioning

confidence: 99%

Systematic approach for the life cycle multi-objective optimization of buildings combining objective reduction and surrogate modeling

Carreras

Pozo

Boer

et al. 2016

Energy and Buildings

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We present a systematic approach to optimize the thermal insulation of a building.  The optimization reduces simultaneously the cost and several environmental impacts.  We resort to an objective reduction method to simplify the problem resolution.  We built a surrogate model to expedite the search for Pareto optimal solutions.  Significant improvements compared to the base case (no insulation) are achieved.

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Section: Moo Of the Surrogate Model In The Reduced Domainmentioning

confidence: 99%

Systematic approach for the life cycle multi-objective optimization of buildings combining objective reduction and surrogate modeling

Carreras

Pozo

Boer

et al. 2016

Energy and Buildings

Self Cite

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“…where There are many methods available to solve multi-objective optimization problems [73][74][75][76]. The solution of a MOO problem is given by a set of points (called Pareto solutions) that represent the optimal trade-off between the objectives considered in the analysis [40,77].…”

Section: Solution Proceduresmentioning

confidence: 99%

Multi-objective optimization of thermal modelled cubicles considering the total cost and life cycle environmental impact

Carreras

Boer

Guillén‐Gosálbez

et al. 2015

Energy and Buildings

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Energy efficiency strategies, such as building insulation, improve the building performance without compromising comfort. This study presents a methodology for determining the optimal insulation thickness for external building surfaces. Our approach is based on a multi-objective optimization model that minimizes simultaneously the cost and environmental impact associated with both the energy consumption over the operational phase and the generation of the construction materials (including the waste produced during the disposal phase). The thermal loads of the modelled cubicles were calculated using EnergyPlus, a widely used simulation program for buildings. The environmental impact was quantified following the life cycle assessment (LCA) methodology. This methodology was applied to a case study of a house-like cubicle located in Lleida (northeast Spain). Taking as a basis a standard cubicle without insulation, our approach identifies solutions that reduce around 40% both, the 2 cost and environmental impact. Optimal solutions show also important economic and environmental improvements compared to cubicles constructed with the Spanish legislation requirements. Our method is intended to assist decision-makers in the design of buildings.

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“…in less than 20 minutes with an optimality gap of 1%. However, bi-level decomposition methods [33][34][35][36]…”

Section: Spatial Decomposition Approachmentioning

confidence: 99%

“…in less than 20 min with an optimality gap of 1%. However, bilevel decomposition methods − could enable the reduction of the required CPU time without significantly affecting the accuracy of the results, through a systematic identification and elimination of redundant criteria from the mathematical formulation. This could also support an extension to optimization under uncertainty.…”

Section: Spatial Decomposition Approachmentioning

confidence: 99%

Supply Chain Mixed Integer Linear Program Model Integrating a Biorefining Technology Superstructure

Panteli

Giarola

Shah

2018

Ind. Eng. Chem. Res.

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A crucial element of the quest of curbing carbon dioxide emissions is deemed to rely on a biobased economy, which will rely on the development of financially sustainable biorefining systems enabling a full exploitation of lignocellulosic biomass (and its macrocomponents, i.e. cellulose, hemicellulose and lignin) for the co-production of biofuels and bioderived platform chemicals. In this work, a general modelling framework conceived to steer decision-making regarding the strategic design and systematic planning of advanced biorefining supply networks is presented. The design task is formulated as a mixed integer linear program (MILP) which accounts for the maximisation of the supply chain profit, considering multi-echelon, multi-period, multi-feedstock and multiproduct aspects as well as spatially explicit features. The applicability of the proposed model, along with the use of a bi-level decomposition approach, are demonstrated with a case study of lignocellulose-based biorefining production systems in the SouthWest of Hungary. Results show the effectiveness of the tool in the decision-making regarding the systematic design of advanced biorefining SC networks. An economic analysis

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MILP-based decomposition algorithm for dimensionality reduction in multi-objective optimization: Application to environmental and systems biology problems

Cited by 21 publications

References 24 publications

Systematic approach for the life cycle multi-objective optimization of buildings combining objective reduction and surrogate modeling

Systematic approach for the life cycle multi-objective optimization of buildings combining objective reduction and surrogate modeling

Multi-objective optimization of thermal modelled cubicles considering the total cost and life cycle environmental impact

Supply Chain Mixed Integer Linear Program Model Integrating a Biorefining Technology Superstructure

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