Interactive Optimization With Parallel Coordinates: Exploring Multidimensional Spaces for Decision Support

Cajot, Sébastien; Schüler, Nils; Peter, Markus; Koch, Andreas; Maréchal, François

doi:10.3389/fict.2018.00032

Cited by 16 publications

(10 citation statements)

References 113 publications

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“…A number of user studies have evaluated the effectiveness of interactive optimisation systems [4,8,10,12,13,15,17,18,23,25,27,30,32,37,45,50,52,56]. In particular, Caldas and Santos [13] developed a user-guided interactive system for daylighting design and found the proposed system could produce good-quality solutions.…”

Section: Interactive Optimisationmentioning

confidence: 99%

“…In order to examine the usefulness of the nine recommendations proposed above, we will now examine (retrospectively) whether the recommendations are met by 15 representative systems from the literature [4,8,10,12,13,15,17,25,27,30,32,45,50,52,56]. The examination is not exhaustive as there many interactive optimisation systems.…”

Section: Reflections Of Design Recommendations In Existing Systemsmentioning

confidence: 99%

“…However, there were two exceptions. Unlike Belin's approach, Cajot et al [12] utilised parallel coordinates in an urban planning problem to facilitate stakeholders' decision making. In machine learning, Kapoor et al [30] used an adjacency matrix to represent the classification result.…”

Section: Reflections Of Design Recommendations In Existing Systemsmentioning

confidence: 99%

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Supporting the Problem-Solving Loop: Designing Highly Interactive Optimisation Systems

Liu

Dwyer

Tack

et al. 2021

IEEE Trans. Visual. Comput. Graphics

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Efficient optimisation algorithms have become important tools for finding high-quality solutions to hard, real-world problems such as production scheduling, timetabling, or vehicle routing. These algorithms are typically "black boxes" that work on mathematical models of the problem to solve. However, many problems are difficult to fully specify, and require a "human in the loop" who collaborates with the algorithm by refining the model and guiding the search to produce acceptable solutions. Recently, the Problem-Solving Loop was introduced as a high-level model of such interactive optimisation. Here, we present and evaluate nine recommendations for the design of interactive visualisation tools supporting the Problem-Solving Loop. They range from the choice of visual representation for solutions and constraints to the use of a solution gallery to support exploration of alternate solutions. We first examined the applicability of the recommendations by investigating how well they had been supported in previous interactive optimisation tools. We then evaluated the recommendations in the context of the vehicle routing problem with time windows (VRPTW). To do so we built a sophisticated interactive visual system for solving VRPTW that was informed by the recommendations. Ten participants then used this system to solve a variety of routing problems. We report on participant comments and interaction patterns with the tool. These showed the tool was regarded as highly usable and the results generally supported the usefulness of the underlying recommendations.

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Section: Interactive Optimisationmentioning

confidence: 99%

Section: Reflections Of Design Recommendations In Existing Systemsmentioning

confidence: 99%

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Supporting the Problem-Solving Loop: Designing Highly Interactive Optimisation Systems

Liu

Dwyer

Tack

et al. 2021

IEEE Trans. Visual. Comput. Graphics

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“…The focus here is on describing the correlation between the workflow and the resulting dataflow. The use case itself is described in detail in (Cajot et al, 2018).…”

Section: Applicationmentioning

confidence: 99%

Linking Interactive Optimization for Urban Planning With a Semantic 3d City Model

Schüler

Agugiaro

Cajot

et al. 2018

ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci.

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Abstract. The cities in which we live are constantly evolving. The active management of this evolution is referred to as urban planning. The according development process could go in many directions resulting in a large number of potential future scenarios of a city. The planning support system URBio adopts interactive optimization to assist urban planners in generating and exploring those various scenarios. As a computer-based system it needs to be able to efficiently handle all underlying data of this exploration process, which includes both methodology-specific and context-specific information. This article describes the work carried out to link URBio with a semantic city model. Therefore, two key requirements were identified and implemented: (a) the extension of the CityGML data model to cope with many scenarios by the proposition of the Scenario Application Domain Extension (ADE) and (b) the definition of a data model for interactive optimization. Classes and features of the developed data models are motivated, depicted and explained. Their usability is demonstrated by walking through a typical workflow of URBio and laying out the induced data flows. The article is concluded with stating further potential applications of both the Scenario ADE and the data model for interactive optimization.

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“…They further allow practitioners to understand why they are selecting a specific solution and how this solution's performance is compared to the rest. Among these tools, parallel coordinates visualization tool [32] is a powerful and practical way for evaluation and decision-making in high-dimensional spaces with applications in urban planning [33,34] and process integration [15]. This tool has been selected to visualize and further select promising alternatives similar to the approach presented by Kermani et al [15].…”

Section: Introductionmentioning

confidence: 99%

Optimal Design of Heat-Integrated Water Allocation Networks

2019

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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.

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Interactive Optimization With Parallel Coordinates: Exploring Multidimensional Spaces for Decision Support

Cited by 16 publications

References 113 publications

Supporting the Problem-Solving Loop: Designing Highly Interactive Optimisation Systems

Supporting the Problem-Solving Loop: Designing Highly Interactive Optimisation Systems

Linking Interactive Optimization for Urban Planning With a Semantic 3d City Model

Optimal Design of Heat-Integrated Water Allocation Networks

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