Journal ArticleDOI
Social structure optimization in team formation
TLDR
This paper describes LK-TFP as a tree search procedure and discusses the reasons of its effectiveness, as well as proposing a methodological toolbox that incorporates social structures into TFP.About:
This article is published in Computers & Operations Research.The article was published on 2016-10-01. It has received 25 citations till now. The article focuses on the topics: Social network analysis & Heuristic (computer science).read more
Citations
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Overcoming human trafficking via operations research and analytics: Opportunities for methods, models, and applications
TL;DR: Some of the unique concerns, problems, and challenges of human trafficking in relation to analytical techniques are described; subsequently, a variety of ways that OR and analytics can be applied in the human trafficking domain are demonstrated.
Journal ArticleDOI
Social Network Analysis With Data Fusion
TL;DR: The reported results shed light on the sensitivity of betweenness, closeness, and degree centrality metrics to fused graph inputs and the role of HVI identification as a test and evaluation tool for fusion process optimization.
Journal ArticleDOI
Observing network characteristics in mass collaboration design projects
Zachary Ball,Kemper Lewis +1 more
TL;DR: This work proposes a simulation framework that evaluates the design potential of a project team based on individual attributes and the team network structure through a generalized simulation framework, applicable to future crowd and design initiatives.
Journal ArticleDOI
A New Optimization Model for Reliable Team Formation Problem Considering Experts’ Collaboration Network
TL;DR: The new optimization model, called the reliable team formation problem, proposed team members in two sets consisting of main and backup members, maximized team reliability by considering the probability of unreliable experts that may leave the team with the probability (1-Q) and proposed a backup for each unreliable member.
Journal ArticleDOI
A multi-objective stochastic programming model for project-oriented human-resource management optimization
TL;DR: A new multi-objective mathematical model for developing a project team for multi-disciplinary projects under uncertainty and its solution methodology can be applied to different types of projects is presented.
References
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Journal ArticleDOI
Statistical mechanics of complex networks
TL;DR: In this paper, a simple model based on the power-law degree distribution of real networks was proposed, which was able to reproduce the power law degree distribution in real networks and to capture the evolution of networks, not just their static topology.
Book
Social Network Analysis: Methods and Applications
TL;DR: This paper presents mathematical representation of social networks in the social and behavioral sciences through the lens of Dyadic and Triadic Interaction Models, which describes the relationships between actor and group measures and the structure of networks.
Journal ArticleDOI
Community structure in social and biological networks
Michelle Girvan,Mark Newman +1 more
TL;DR: This article proposes a method for detecting communities, built around the idea of using centrality indices to find community boundaries, and tests it on computer-generated and real-world graphs whose community structure is already known and finds that the method detects this known structure with high sensitivity and reliability.
Journal ArticleDOI
Structural Holes: The Social Structure of Competition.
Steven B. Andrews,Ronald S. Burt +1 more
TL;DR: In this article, structural holes are defined as network gaps between players which create entrepreneurial opportunities for information access, timing, referrals, and for control, and the structural holes also generate control benefits giving certain players an advantage in negotiating their relationships.
Book
Structural Holes: The Social Structure of Competition
TL;DR: In this paper, the Tertius Gaudens Entrepreneurs Secondary Holes Structural Autonomy (SSA) model is used to control the number of holes in a network.