Conference scheduling — A personalized approach

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

doi:10.1016/j.omega.2017.09.007

Cited by 20 publications

(13 citation statements)

References 19 publications

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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 (Tanaka, Mori & Bargiela, 2002) 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: Related Workmentioning

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.…”

Section: Introductionmentioning

confidence: 99%

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Avoiding “conflicts of interest”: a computational approach to scheduling parallel conference tracks and its human evaluation

Manda

Hahn

Beekman³

2019

PeerJ Computer Science

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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 1,000 contributed talks plus scheduling constraints. In a randomized experiment, biologists responded similarly to a machine-optimized schedule and a highly modified schedule produced by domain experts on the conference program committee.

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Section: Related Workmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Avoiding “conflicts of interest”: a computational approach to scheduling parallel conference tracks and its human evaluation

Manda

Hahn

Beekman³

2019

PeerJ Computer Science

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“…The host agent then follow a certain heuristics to generate an optimal schedule. Heuristics is used to find a satisfactory solution which is considered optimal, finding the real optimal solution might need a complex computation [8]. The goal is to maximize a certain score function [3].…”

Section: Aswin Wibisurya Ikhtiar Faahakhododomentioning

confidence: 99%

“…The goal is to maximize a certain score function [3]. The variable to be scored in a heuristics can be participants' preference rate [6], participants' availability (minimizing conflicting schedule) [2], [9], room availability [8], or energy efficiency [3], [4]. This heuristics approach is more common in a dynamic environment.…”

Section: Aswin Wibisurya Ikhtiar Faahakhododomentioning

confidence: 99%

Meeting Scheduling Application using Availability and Priority Attendance Heuristics

Wibisurya,

Faahakhododo

2019

IJEAT

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Meeting scheduling is a repetitive and time consuming task for many organizations. Emails and electronic calendars has been used to help a meeting host in this process. However, it does not automate the process of searching the optimal time slot. Manual scheduling may result in suboptimal schedule. Therefore, automation is needed for meeting scheduling problem. The purpose of this research is to propose an applied model consisting of both acquiring participants’ existing schedule, and searching for an optimal time slot. Previous studies groups the solution of meeting scheduling into either constraint satisfaction or heuristics approach. Heuristics is more appropriate for a dynamic environment. The heuristics-based model is designed to consider participant availability and participant prioritization. The more participants are available, the better the time is as a candidate for optimum schedule. In the proposed model, the availability of certain key person, experts, or host may carry more weight than normal participant. An Android based application is developed as a prove of concept of the proposed model. Google Calendar API is used in this model to acquire the existing schedule, then each time slot is assigned a score based on availability weighting. The time slot with the highest score is considered the optimal solution. Evaluation is done by simulating the scheduling part for various numbers of meetings and time slots. The result shows that the model is capable of searching the optimal meeting schedule in less than one second for each of the experiment.

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Effectiveness of Genetic Algorithm in the Solution of Multidisciplinary Conference Scheduling Problem

Atagün

Biroğul

2021

Trends in Data Engineering Methods for Intelligent Systems

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Conference scheduling — A personalized approach

Cited by 20 publications

References 19 publications

Avoiding “conflicts of interest”: a computational approach to scheduling parallel conference tracks and its human evaluation

Avoiding “conflicts of interest”: a computational approach to scheduling parallel conference tracks and its human evaluation

Meeting Scheduling Application using Availability and Priority Attendance Heuristics

Effectiveness of Genetic Algorithm in the Solution of Multidisciplinary Conference Scheduling Problem

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