Hierarchical clustering is a recursive partitioning of a dataset into clusters at an increasingly finer granularity. Motivated by the fact that most work on hierarchical clustering was based on providing algorithms, rather than optimizing a specific objective, [19] framed similarity-based hierarchical clustering as a combinatorial optimization problem, where a ‘good’ hierarchical clustering is ...

Most static mixers are designed to maximize radial mixing to achieve compositional and thermal homogeneity. Flow inverters maximize heat transfer. Axial mixers that closely approximate an exponential distribution of residence times have been devised as well. More recent papers describe static mixers for surge dampening in industrial swing-cycle processes (Smith, Graham, and Palamara, 2006). An ...

We present the first fast route planning algorithm that answers shortest paths queries for a customizable linear combination of two different metrics, e. g. travel time and energy cost, on large scale road networks. The precomputation receives as input a directed graph, two edge weight functions t(e) and c(e), and a discrete interval [L,U ]. The resulting flexible query algorithm finds for a pa...

strategic programming, complex supply chain, lean, production programming, suppliers selection,   electre this paper represents a model of strategic programming with limited resources in a complex supply chain. the main goal of the proposed model is to increase efficiency and effectiveness of the supply chain with respect to income increases and cost decreases. using special objective functions...