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

2019 ◽  
Vol 5 ◽  
pp. e234
Author(s):  
Prashanti Manda ◽  
Alexander Hahn ◽  
Katherine Beekman ◽  
Todd J. Vision
Keyword(s):  
Objective Function ◽  
Topic Model ◽  
Conflicts Of Interest ◽  
Program Committee ◽  
Heuristic Optimization ◽  
Test Case ◽  
Scheduling Problem ◽  
Domain Experts ◽  
Human Evaluation ◽  
Optimized Schedule

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.

scholarly journals Avoiding "conflicts of interest'': A computational approach to scheduling parallel conference tracks and its human evaluation

2019 ◽  
Author(s):  
Prashanti Manda ◽  
Alexander Hahn ◽  
Katherine Lamm ◽  
Scott Provan ◽  
Todd J Vision
Keyword(s):  
Objective Function ◽  
Topic Model ◽  
Conflicts Of Interest ◽  
Program Committee ◽  
Heuristic Optimization ◽  
Test Case ◽  
Scheduling Problem ◽  
Domain Experts ◽  
Order Of Magnitude ◽  
Optimized Schedule

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 simulated annealing improves the objective function over an order of magnitude 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 modified schedule produced by domain experts on the conference program committee.

scholarly journals Avoiding "conflicts of interest'': A computational approach to scheduling parallel conference tracks and its human evaluation

2019 ◽  
Author(s):  
Prashanti Manda ◽  
Alexander Hahn ◽  
Katherine Lamm ◽  
Scott Provan ◽  
Todd J Vision
Keyword(s):  
Objective Function ◽  
Topic Model ◽  
Conflicts Of Interest ◽  
Program Committee ◽  
Heuristic Optimization ◽  
Test Case ◽  
Scheduling Problem ◽  
Domain Experts ◽  
Order Of Magnitude ◽  
Optimized Schedule

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 simulated annealing improves the objective function over an order of magnitude 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 modified schedule produced by domain experts on the conference program committee.

The surveillance of a supreme audit institution on related party transactions

2020 ◽  
Vol 32 (4) ◽  
pp. 577-603
Author(s):  
Gustavo Cesário ◽  
Ricardo Lopes Cardoso ◽  
Renato Santos Aranha
Keyword(s):  
Public Sector ◽  
Latent Dirichlet Allocation ◽  
Topic Model ◽  
Conflicts Of Interest ◽  
International Standards ◽  
Content Type ◽  
Related Party Transactions ◽  
The Public ◽  
Audit Reports ◽  
Dirichlet Allocation

PurposeThis paper aims to analyse how the supreme audit institution (SAI) monitors related party transactions (RPTs) in the Brazilian public sector. It considers definitions and disclosure policies of RPTs by international accounting and auditing standards and their evolution since 1980.Design/methodology/approachBased on archival research on international standards and using an interpretive approach, the authors investigated definitions and disclosure policies. Using a topic model based on latent Dirichlet allocation, the authors performed a content analysis on over 59,000 SAI decisions to assess how the SAI monitors RPTs.FindingsThe SAI investigates nepotism (a kind of RPT) and conflicts of interest up to eight times more frequently than related parties. Brazilian laws prevent nepotism and conflicts of interest, but not RPTs in general. Indeed, Brazilian public-sector accounting standards have not converged towards IPSAS 20, and ISSAI 1550 does not adjust auditing procedures to suit the public sector.Research limitations/implicationsThe SAI follows a legalistic auditing approach, indicating a need for regulation of related public-sector parties to improve surveillance. In addition to Brazil, other code law countries might face similar circumstances.Originality/valuePublic-sector RPTs are an under-investigated field, calling for attention by academics and standard-setters. Text mining and latent Dirichlet allocation, while mature techniques, are underexplored in accounting and auditing studies. Additionally, the Python script created to analyse the audit reports is available at Mendeley Data and may be used to perform similar analyses with minor adaptations.

Modeling and Simulation of Holonic Meta-Algorithm in Scheduling Process Using PERT Technique − Optimization in Job Shop Scheduling Problem

2015 ◽  
Vol 760 ◽  
pp. 199-204
Author(s):  
Mircea Gorgoi ◽  
Corneliu Neagu
Keyword(s):  
Objective Function ◽  
Job Shop ◽  
Job Shop Scheduling ◽  
Scheduling Problem ◽  
Job Shop Scheduling Problem ◽  
New Approach ◽  
Shop Scheduling ◽  
Technique Optimization ◽  
Optimum Solution

In generally scheduling can be viewed as optimization, bound by sequence and resource constrain and the minimization of the makespan is often used as the criterion. In this paper minimization of the makespan or complete time will be used such as an objective function and not the criterion of the decision. The new approach use heuristic elementary priority dispatch rules as the criterion of the decision. This research purpose a new methodology which use a specific elements of PERT techniques to find the optimum solution. New approach establish a solution's space where are find the all solution of the problem. Determination of the solution's space is realized by a meta-algorithm which take in account all the variant of the solutions of the process.

scholarly journals Minimization of Machine Idle Time and Penalty Cost in Flexible Manufacturing System Scheduling

2019 ◽  
Vol 8 (6) ◽  
pp. 483-487
Keyword(s):  
Objective Function ◽  
Flexible Manufacturing ◽  
Manufacturing System ◽  
Flexible Manufacturing System ◽  
Cuckoo Search ◽  
Scheduling Problem ◽  
Jaya Algorithm ◽  
Penalty Cost ◽  
Paper Address ◽  
Better Than

This paper address the application of Jaya algorithm to solve Multi objective scheduling problem in Flexible Manufacturing System(FMS) to Minimize the Combined Objective Function(COF) Value. The effectiveness of this algorithm is tested on the problem of 43 jobs processed on 16 machines taken from literature. The MATLAB code is written to find best sequence and Combined Objective Function value by implementing Jaya Algorithm. Results obtained by Jaya Algorithm are compared with different algorithms such as Genetic Algorithms (GA), Particle Swarm Optimization (PSO), Shortest Processing Time (SPT), Cuckoo Search (CS) and Modified Cuckoos Search (MCS) for the problem considered. It is observed from the results that COF value for the sequence obtained by Jaya Algorithm is better than other algorithms. It is concluded that the Jaya algorithm is best suitable for solving the Scheduling problem considered in Flexible Manufacturing System.

Scheduling Problem for Parallel Machines with Limited Processing Capacities

2011 ◽  
Vol 382 ◽  
pp. 110-113
Author(s):  
Jing Fan
Keyword(s):  
Approximation Algorithms ◽  
Objective Function ◽  
Completion Time ◽  
Parallel Machines ◽  
Industrial Engineering ◽  
Scheduling Problem ◽  
Np Hard ◽  
The Novel

In the actual industrial engineering, machines used for processing need to be checked periodically to ensure that they can work efficiently. Thus, the novel scheduling problem for parallel machines with limited capacities is worth to study. The objective function is to maximize the last completion time of jobs. We show the problem is NP-hard at least. Furthermore, two approximation algorithms are presented, and algorithms' performances are considered through the experiments with large amounts of data.

scholarly journals UPFC Location and Performance Analysis in Deregulated Power Systems

2009 ◽  
Vol 2009 ◽  
pp. 1-20 ◽  
Author(s):  
Seyed Abbas Taher ◽  
Ali Akbar Abrishami
Keyword(s):  
Power Systems ◽  
Objective Function ◽  
Electricity Market ◽  
Power Flow ◽  
Reactive Power ◽  
Unified Power Flow Controller ◽  
Test Case ◽  
Spot Prices ◽  
Sensitivity Approach ◽  
The Impact

We deal with the effect of Unified Power Flow Controller (UPFC) installation on the objective function of an electricity market. Also this paper proposes a Novel UPFC modelling in OPF which facilities the consideration of the impact of four factors on power market. These include the series transformer impedance addition, the shunt reactive power injection, the in-phase component of the series voltage and the quadrature component of the series voltage. The impact of each factor on the electricity market objective function is measured and then compared with the results from a sensitivity approach. The proposed sensitivity approach is fast so it does not need to repeat OPF solutions. The total impacts of the factors are used to offer UPFC insertion candidate points. It is shown that there is a clear match between the candidate points of the sensitivity method and those proposed by the introduced UPFC modelling in our test case. Furthermore, based on the proposed method, the relation between settings of UPFC series part and active and reactive power spot prices is presented.

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