Journal ArticleDOI
Partitioning procedures for solving mixed-variables programming problems
TLDR
This paper presented to the 8th International Meeting of the Institute of Management Sciences, Brussels, August 23-26, 1961 presents a meta-analyses of the determinants of infectious disease in eight operation rooms of the immune system and its consequences.Abstract:
Paper presented to the 8th International Meeting of the Institute of Management Sciences, Brussels, August 23-26, 1961.read more
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Distributed Optimization and Statistical Learning Via the Alternating Direction Method of Multipliers
TL;DR: It is argued that the alternating direction method of multipliers is well suited to distributed convex optimization, and in particular to large-scale problems arising in statistics, machine learning, and related areas.
Book
Metaheuristics: From Design to Implementation
TL;DR: This book provides a complete background on metaheuristics and shows readers how to design and implement efficient algorithms to solve complex optimization problems across a diverse range of applications, from networking and bioinformatics to engineering design, routing, and scheduling.
Book
Routing, Flow, And Capacity Design In Communication And Computer Networks
Michal Pioro,Deepankar Medhi +1 more
TL;DR: Throughout, the authors focus on the traffic demands encountered in the real world of network design, and their generic approach allows problem formulations and solutions to be applied across the board to virtually any type of backbone communication or computer network.
Integer and Combinatorial Optimization
Karla Hoffman,Ted K. Ralphs +1 more
TL;DR: In today’s changing and competitive industrial environment, the difference between ad hoc planning methods and those that use sophisticated mathematical models to determine an optimal course of action can determine whether or not a company survives.
Journal ArticleDOI
A stochastic programming approach for supply chain network design under uncertainty
TL;DR: This paper proposes a stochastic programming model and solution algorithm for solving supply chain network design problems of a realistic scale and integrates a recently proposed sampling strategy, the sample average approximation scheme, with an accelerated Benders decomposition algorithm to quickly compute high quality solutions.