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

Atagün, Ercan; Biroğul, Serdar

doi:10.1007/978-3-030-79357-9_22

Cited by 1 publication

(1 citation statement)

References 15 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Meeting scheduling has focused more on optimizing participation, fairness has received little attention in such settings (except for Baum et al [4] dealing with a very different context). Besides there have been very few works on conference scheduling, but they focus on in-person settings [28,32] and efficiency objectives [3,7]. Our mFairConf framework not only accommodates satisfaction of participants and speakers, but also cares for both efficiency and fairness in conference scheduling.…”

Section: Related Workmentioning

confidence: 99%

Scheduling Virtual Conferences Fairly: Achieving Equitable Participant and Speaker Satisfaction

Patro,

Jana,

Chakraborty

et al. 2022

Preprint

View full text Add to dashboard Cite

Recently, almost all conferences have moved to virtual mode due to the pandemic-induced restrictions on travel and social gathering. Contrary to in-person conferences, virtual conferences face the challenge of efficiently scheduling talks, accounting for the availability of participants from different timezones and their interests in attending different talks. A natural objective for conference organizers is to maximize efficiency, e.g., total expected audience participation across all talks. However, we show that optimizing for efficiency alone can result in an unfair virtual conference schedule, where individual utilities for participants and speakers can be highly unequal. To address this, we formally define fairness notions for participants and speakers, and derive suitable objectives to account for them. As the efficiency and fairness objectives can be in conflict with each other, we propose a joint optimization framework that allows conference organizers to design schedules that balance (i.e., allow trade-offs) among efficiency, participant fairness and speaker fairness objectives. While the optimization problem can be solved using integer programming to schedule smaller conferences, we provide two scalable techniques to cater to bigger conferences. Extensive evaluations over multiple real-world datasets show the efficacy and flexibility of our proposed approaches. CCS CONCEPTS• Theory of computation → Scheduling algorithms.

show abstract