TY - JOUR
T1 - Supporting the Problem-Solving Loop
T2 - designing highly interactive optimisation systems
AU - Liu, Jie
AU - Dwyer, Tim
AU - Tack, Guido
AU - Gratzl, Samuel
AU - Marriott, Kim
PY - 2021/2
Y1 - 2021/2
N2 - 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.
AB - 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.
KW - Interactive optimisation
KW - Interactive systems and tools
KW - Interface design
KW - Usability
KW - Vehicle routing
UR - http://www.scopus.com/inward/record.url?scp=85100404595&partnerID=8YFLogxK
U2 - 10.1109/TVCG.2020.3030364
DO - 10.1109/TVCG.2020.3030364
M3 - Article
C2 - 33112748
AN - SCOPUS:85100404595
SN - 1077-2626
VL - 27
SP - 1764
EP - 1774
JO - IEEE Transactions on Visualization and Computer Graphics
JF - IEEE Transactions on Visualization and Computer Graphics
IS - 2
ER -