Post-processing & interactive visualisation of optimisation results. Deliverable D5.2 of the EU Horizon 2020 project OPTAIN

Deliverable report D5.2 of the EU Horizon 2020 Project OPTAIN (Grant agreement No. 862756) Summary Multi-objective optimisation is a powerful approach for generating a set of Pareto optimal design alternatives that decision-makers can evaluate in order to select the most-suitable configuration. In practice, however, selecting from a large number of Pareto optimal solutions can be daunting. The objective of this report is to enable researchers and stakeholders to assess the optimisation outputs produced in OPTAINs previous Task 5.2 in a structured manner, to render the results tangible and understandable, and to maximise their use for the subsequent stakeholder consultation. This report describes the tool ParetoPick-R, including how to run it, its data input requirements and the processes it employs. ParetoPick-R allows (1) to make the complex optimisation outputs understandable through various intuitive visualisation techniques, including for the links between the objective space and the decision space of Natural/Small Water Retention Measures (NSWRM) implementation plans. (2) It implements a methodology for reducing the high number of solutions from the previous optimisation to a manageable number while reducing information loss, and (3) allows to perform an Analytical Hierarchy Process for stakeholders to assign priorities based on pairwise preferences in a structured manner. This report is useful for researchers and stakeholders from OPTAIN and beyond working with complex optimisation problems who want to analyse their results in a structured and meaningful way and render them actionable.

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Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2025-02-28
DOI
https://doi.org/10.5281/zenodo.15043865
Primary Topic
Advanced Multi-Objective Optimization Algorithms
Type
article
Field-Weighted Citation Impact
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article

Post-processing & interactive visualisation of optimisation results. Deliverable D5.2 of the EU Horizon 2020 project OPTAIN

Zenodo (CERN European Organization for Nuclear Research)
Advanced Multi-Objective Optimization Algorithms
article

Post-processing & interactive visualisation of optimisation results. Deliverable D5.2 of the EU Horizon 2020 project OPTAIN

article en

Abstract

Deliverable report D5.2 of the EU Horizon 2020 Project OPTAIN (Grant agreement No. 862756) Summary Multi-objective optimisation is a powerful approach for generating a set of Pareto optimal design alternatives that decision-makers can evaluate in order to select the most-suitable configuration. In practice, however, selecting from a large number of Pareto optimal solutions can be daunting. The objective of this report is to enable researchers and stakeholders to assess the optimisation outputs produced in OPTAINs previous Task 5.2 in a structured manner, to render the results tangible and understandable, and to maximise their use for the subsequent stakeholder consultation. This report describes the tool ParetoPick-R, including how to run it, its data input requirements and the processes it employs. ParetoPick-R allows (1) to make the complex optimisation outputs understandable through various intuitive visualisation techniques, including for the links between the objective space and the decision space of Natural/Small Water Retention Measures (NSWRM) implementation plans. (2) It implements a methodology for reducing the high number of solutions from the previous optimisation to a manageable number while reducing information loss, and (3) allows to perform an Analytical Hierarchy Process for stakeholders to assign priorities based on pairwise preferences in a structured manner. This report is useful for researchers and stakeholders from OPTAIN and beyond working with complex optimisation problems who want to analyse their results in a structured and meaningful way and render them actionable.

Zenodo (CERN European Organization for Nuclear Research)
Helmholtz Centre for Environmental Research (DE)
Openalex Percentile: Top 53%
Advanced Multi-Objective Optimization Algorithms
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