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Operational Research: methods and applications
Abstract Throughout its history, Operational Research has evolved to include methods,
models and algorithms that have been applied to a wide range of contexts. This …
models and algorithms that have been applied to a wide range of contexts. This …
Frontiers in service science: Ride matching for peer-to-peer ride sharing: A review and future directions
As a consequence of the sharing economy attaining more popularity, there has been a shift
toward shared-use mobility services in recent years, especially those that encourage users …
toward shared-use mobility services in recent years, especially those that encourage users …
Maximum flow and minimum-cost flow in almost-linear time
We give an algorithm that computes exact maximum flows and minimum-cost flows on
directed graphs with m edges and polynomially bounded integral demands, costs, and …
directed graphs with m edges and polynomially bounded integral demands, costs, and …
A deterministic almost-linear time algorithm for minimum-cost flow
We give a deterministic m^1+o(1) time algorithm that computes exact maximum flows and
minimum-cost flows on directed graphs with m edges and polynomially bounded integral …
minimum-cost flows on directed graphs with m edges and polynomially bounded integral …
Sinkhorn distances: Lightspeed computation of optimal transport
M Cuturi - Advances in neural information processing …, 2013 - proceedings.neurips.cc
Optimal transportation distances are a fundamental family of parameterized distances for
histograms in the probability simplex. Despite their appealing theoretical properties …
histograms in the probability simplex. Despite their appealing theoretical properties …
Minimum cost flows, MDPs, and ℓ1-regression in nearly linear time for dense instances
In this paper we provide new randomized algorithms with improved runtimes for solving
linear programs with two-sided constraints. In the special case of the minimum cost flow …
linear programs with two-sided constraints. In the special case of the minimum cost flow …
Conditional gradient methods
G Braun, A Carderera, CW Combettes… - arxiv preprint arxiv …, 2022 - arxiv.org
The purpose of this survey is to serve both as a gentle introduction and a coherent overview
of state-of-the-art Frank--Wolfe algorithms, also called conditional gradient algorithms, for …
of state-of-the-art Frank--Wolfe algorithms, also called conditional gradient algorithms, for …
Path finding methods for linear programming: Solving linear programs in o (vrank) iterations and faster algorithms for maximum flow
In this paper, we present a new algorithm for'/solving linear programs that requires only Õ
(√ rank (A) L) iterations where A is the constraint matrix of a linear program with m …
(√ rank (A) L) iterations where A is the constraint matrix of a linear program with m …
Resource-constrained project scheduling: Notation, classification, models, and methods
P Brucker, A Drexl, R Möhring, K Neumann… - European journal of …, 1999 - Elsevier
Project scheduling is concerned with single-item or small batch production where scarce
resources have to be allocated to dependent activities over time. Applications can be found …
resources have to be allocated to dependent activities over time. Applications can be found …
Fast and robust earth mover's distances
We present a new algorithm for a robust family of Earth Mover's Distances-EMDs with
thresholded ground distances. The algorithm transforms the flow-network of the EMD so that …
thresholded ground distances. The algorithm transforms the flow-network of the EMD so that …