The paper proposes a two-stage approach that combines data mining and complex network
theory to optimize the locations and service areas of dry ports in a large-scale inland …

Community detection in social networks is a fundamental task of complex network analysis.
Community is usually regarded as a functional unit. Networks in real world more or less …

This paper deals with the k-way normalized cut problem in complex networks. It presents a
methodology that uses mathematical optimization to provide mixed-integer linear …

Modularity density maximization is a community detection optimization problem which
improves the resolution limit degeneracy of modularity maximization. This paper presents …

Community detection is one of the fundamental tasks in graph mining, which has many real-
world applications in diverse domains. In this study, we propose an optimization model for …

The health and economic devastation caused by the COVID-19 pandemic has created a
significant global humanitarian disaster. Pandemic response policies guided by geospatial …

Modularity density maximization is a clustering method that improves some issues of the
commonly used modularity maximization approach. Recently, some Mixed-Integer Linear …

Cell formation in cellular manufacturing is a critical step to improving productivity by
grou** parts and machines. Numerous heuristic search algorithms and several …

Community detection is a fundamental network-analysis primitive with a variety of
applications in diverse domains. Although the modularity introduced by Newman and Girvan …

For clustering of an undirected graph, this paper presents an exact algorithm for the
maximization of modularity density, a more complicated criterion that overcomes drawbacks …