Conference Scheduling   A Personalized Approach

Vangerven, Bart; Ficker, Annette; Goossens, Dries; Passchyn, Ward; Spieksma, Frits; Woeginger, Gerhard J.

doi:10.2139/ssrn.2937631

Cited by 2 publications

(3 citation statements)

References 21 publications

(18 reference statements)

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“…Surprisingly, given the pervasive exposure of academics to the challenges of conference scheduling, there is a relatively small literature on the problem (reviewed in Vangerven et al [2018]). Bhardwaj et al [2014] and André et al [2013] incorporate attendee preferences for talk and session placement in a Community-Informed Conference Scheduling approach [Sampson, 2009;Kim et al, 2013;Chilton et al, 2014].…”

Section: Related Workmentioning

confidence: 99%

“…They use Kohonen's self organizing maps and a hybrid grouping genetic algorithm . Vangerven et al [2018] present a method that approaches the conference scheduling problem in three phases. The first phase aims to maximize total attendance, based on the participants' preferences.…”

Section: /22mentioning

confidence: 99%

“…Ensuring a high level of dissimilarity among concurrent sessions is important to minimize participants having to move between sessions, or having to choose between co-occurring talks of equal interest. Vangerven et al [2018] also note that dissimilarity between concurrent sessions is important for enabling participants to attend the talks of most interest to them without encountering scheduling conflicts, as might happen when talks of a similar topical nature are scheduled in concurrent sessions.…”

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confidence: 99%

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Peer Review #2 of "Avoiding “conflicts of interest”: a computational approach to scheduling parallel conference tracks and its human evaluation (v0.1)"

2019

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Conferences with contributed talks grouped into multiple concurrent sessions pose an interesting scheduling problem. From an attendee's perspective, choosing which talks to visit when there are many concurrent sessions is challenging since an individual may be interested in topics that are discussed in different sessions simultaneously. The frequency of topically similar talks in different concurrent sessions is, in fact, a common cause for complaint in post-conference surveys. Here, we introduce a practical solution to the conference scheduling problem by heuristic optimization of an objective function that weighs the occurrence of both topically similar talks in one session and topically different talks in concurrent sessions. Rather than clustering talks based on a limited number of preconceived topics, we employ a topic model to allow the topics to naturally emerge from the corpus of contributed talk titles and abstracts. We then measure the topical distance between all pairs of talks. Heuristic optimization of preliminary schedules seeks to balance the topical similarity of talks within a session and the dissimilarity between concurrent sessions. Using an ecology conference as a test case, we find that stochastic optimization dramatically improves the objective function relative to the schedule manually produced by the program committee. Approximate Integer Linear Programming can be used to provide a partially-optimized starting schedule, but the final value of the discrimination ratio (an objective function used to estimate coherence within a session and disparity between concurrent sessions) is surprisingly insensitive to the starting schedule. Furthermore, we show that, in contrast to the manual process, arbitrary scheduling constraints are straightforward to include. We applied our method to a second biology conference with over 1000 contributed talks plus scheduling constraints. In a randomized experiment, biologists responded similarly to a machine-optimized schedule and a highly

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Section: Related Workmentioning

confidence: 99%

Section: /22mentioning

confidence: 99%

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