When immediate interactive feedback boosts optimization problem solving: a ‘human-in-the-loop’ approach for solving capacitated vehicle routing problems
In past, feedback in problem solving was found to improve human performance and focused mainly on learning applications. Interactive tools supporting decision-making and general problem-solving processes have long being developed to assist operations but not in optimization problem solving. Optimiza...
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| Format: | Article |
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Elsevier
2017
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| Online Access: | https://eprints.nottingham.ac.uk/41607/ |
| _version_ | 1848796313889538048 |
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| author | Kefalidou, Genovefa |
| author_facet | Kefalidou, Genovefa |
| author_sort | Kefalidou, Genovefa |
| building | Nottingham Research Data Repository |
| collection | Online Access |
| description | In past, feedback in problem solving was found to improve human performance and focused mainly on learning applications. Interactive tools supporting decision-making and general problem-solving processes have long being developed to assist operations but not in optimization problem solving. Optimization problem solving is currently addressed within Operational Research (OR) through computational algorithms that aim to find the best solution in a problem (e.g. routing problem). Limited investigation there is on how computerized interactivity and metacognitive support (e.g. feedback and planning) can support optimization problem solving. This paper reports on human performance on Capacitated Vehicle Routing Problems (CVRPs) using paper-based problems and two different versions of an interactive computerized tool (one version with live explanatory and directive feedback alongside planning (strategy) support; one version without strategy support but with live explanatory feedback). Results suggest that human performance did not change when people were given paper-based post-problem feedback. On the contrary, participants' performance improved significantly when they used either version of the interactive tool that facilitated both live feedback support. No differences in performance across the two versions were observed. Implications on current theories and design implications for future optimization systems are discussed. |
| first_indexed | 2025-11-14T19:46:00Z |
| format | Article |
| id | nottingham-41607 |
| institution | University of Nottingham Malaysia Campus |
| institution_category | Local University |
| last_indexed | 2025-11-14T19:46:00Z |
| publishDate | 2017 |
| publisher | Elsevier |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | nottingham-416072020-05-04T19:56:15Z https://eprints.nottingham.ac.uk/41607/ When immediate interactive feedback boosts optimization problem solving: a ‘human-in-the-loop’ approach for solving capacitated vehicle routing problems Kefalidou, Genovefa In past, feedback in problem solving was found to improve human performance and focused mainly on learning applications. Interactive tools supporting decision-making and general problem-solving processes have long being developed to assist operations but not in optimization problem solving. Optimization problem solving is currently addressed within Operational Research (OR) through computational algorithms that aim to find the best solution in a problem (e.g. routing problem). Limited investigation there is on how computerized interactivity and metacognitive support (e.g. feedback and planning) can support optimization problem solving. This paper reports on human performance on Capacitated Vehicle Routing Problems (CVRPs) using paper-based problems and two different versions of an interactive computerized tool (one version with live explanatory and directive feedback alongside planning (strategy) support; one version without strategy support but with live explanatory feedback). Results suggest that human performance did not change when people were given paper-based post-problem feedback. On the contrary, participants' performance improved significantly when they used either version of the interactive tool that facilitated both live feedback support. No differences in performance across the two versions were observed. Implications on current theories and design implications for future optimization systems are discussed. Elsevier 2017-08 Article PeerReviewed Kefalidou, Genovefa (2017) When immediate interactive feedback boosts optimization problem solving: a ‘human-in-the-loop’ approach for solving capacitated vehicle routing problems. Computers in Human Behavior, 73 . pp. 110-124. ISSN 0747-5632 Human-in-the-loop; Interactive route optimization; Human performance; Concurrent feedback; Metacognition http://www.sciencedirect.com/science/article/pii/S0747563217301656 doi:10.1016/j.chb.2017.03.019 doi:10.1016/j.chb.2017.03.019 |
| spellingShingle | Human-in-the-loop; Interactive route optimization; Human performance; Concurrent feedback; Metacognition Kefalidou, Genovefa When immediate interactive feedback boosts optimization problem solving: a ‘human-in-the-loop’ approach for solving capacitated vehicle routing problems |
| title | When immediate interactive feedback boosts optimization problem solving: a ‘human-in-the-loop’ approach for solving capacitated vehicle routing problems |
| title_full | When immediate interactive feedback boosts optimization problem solving: a ‘human-in-the-loop’ approach for solving capacitated vehicle routing problems |
| title_fullStr | When immediate interactive feedback boosts optimization problem solving: a ‘human-in-the-loop’ approach for solving capacitated vehicle routing problems |
| title_full_unstemmed | When immediate interactive feedback boosts optimization problem solving: a ‘human-in-the-loop’ approach for solving capacitated vehicle routing problems |
| title_short | When immediate interactive feedback boosts optimization problem solving: a ‘human-in-the-loop’ approach for solving capacitated vehicle routing problems |
| title_sort | when immediate interactive feedback boosts optimization problem solving: a ‘human-in-the-loop’ approach for solving capacitated vehicle routing problems |
| topic | Human-in-the-loop; Interactive route optimization; Human performance; Concurrent feedback; Metacognition |
| url | https://eprints.nottingham.ac.uk/41607/ https://eprints.nottingham.ac.uk/41607/ https://eprints.nottingham.ac.uk/41607/ |