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Pyomo - Optimization Modeling in Python
This book provides a complete and comprehensive reference/guide to Pyomo (Python Optimization Modeling Objects) for both beginning and advanced modelers, including students at the undergraduate and graduate levels, academic researchers, and practitioners. Expand
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Progressive hedging innovations for a class of stochastic mixed-integer resource allocation problems
Progressive hedging is a scenario-based decomposition technique that can be leveraged to solve multi-stage stochastic programs with integer variables in one or more of the stages. Expand
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The Battle of the Water Sensor Networks "BWSN…: A Design Challenge for Engineers and Algorithms
Following the events of September 11, 2001, in the United States, world public awareness for possible terrorist attacks on water supply systems has increased dramatically. Among the different threatsExpand
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Pyomo: modeling and solving mathematical programs in Python
We describe Pyomo, an open source software package for modeling and solving mathematical programs in Python. Expand
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Sensor Placement in Municipal Water Networks with Temporal Integer Programming Models
We present a mixed-integer programming (MIP) formulation for sensor placement optimization in municipal water distribution systems that includes the temporal characteristics of contamination eventsExpand
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Scheduling Space–Ground Communications for the Air Force Satellite Control Network
We present the first coupled formal and empirical analysis of the Satellite Range Scheduling application and show that it is NP-complete. Expand
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Obtaining lower bounds from the progressive hedging algorithm for stochastic mixed-integer programs
We present a method for computing lower bounds in the progressive hedging algorithm (PHA) for two-stage and multi-stage stochastic mixed-integer programs. Expand
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Contrasting Structured and Random Permutation Flow-Shop Scheduling Problems: Search-Space Topology and Algorithm Performance
We introduce a method for generating structured flow-shop problems, which are modeled after features found in some real-world manufacturing environments. Expand
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Two-stage robust optimization for N-k contingency-constrained unit commitment
This paper proposes a two-stage robust optimization approach to solve the N- k contingency-constrained unit commitment (CCUC) problem. Expand
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Multi-Stage Robust Unit Commitment Considering Wind and Demand Response Uncertainties
With the increasing penetration of wind power into the power grid, maintaining system reliability has been a challenging issue for ISOs/RTOs, due to the intermittent nature of wind power. In additionExpand
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