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ADVANCES IN MATHEMATICAL PROGRAMMING MODELS FOR ENTERPRISEWIDE OPTIMIZATION
"... Enterprisewide optimization (EWO) is an area that lies at the interface of chemical engineering and operations research, and has become a major goal in the process industries due to the increasing pressures for remaining competitive in the global marketplace. EWO involves optimizing the operations ..."
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Enterprisewide optimization (EWO) is an area that lies at the interface of chemical engineering and operations research, and has become a major goal in the process industries due to the increasing pressures for remaining competitive in the global marketplace. EWO involves optimizing the operations of supply, manufacturing and distribution activities of a company to reduce costs, inventories and environmental impact, and to maximize profits and responsiveness. A major focus in EWO is the optimal operation of manufacturing facilities that often require the use of nonlinear process models. Major operational items include planning, scheduling, realtime optimization and control. We provide an overview of EWO in terms of a mathematical programming framework. We first provide a brief overview of mathematical programming techniques (mixedinteger linear and nonlinear optimization methods), as well as decomposition methods, stochastic programming and modeling systems. We then address some of the major issues involved in the modeling and solution of these problems. Finally,
MINLP Solver Software
, 2010
"... In this article we will give a brief overview of the startoftheart on software for the solution of mixed integer nonlinear programs (MINLP). We establish several groupings with respect to various features and give concise individual descriptions for each solver. ..."
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In this article we will give a brief overview of the startoftheart on software for the solution of mixed integer nonlinear programs (MINLP). We establish several groupings with respect to various features and give concise individual descriptions for each solver.
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The public reporting burden lor this collection of information is estimated to average 1 hour per response, including the tin.. „....•uwwtn/tto, »4iumng existing data sources gathering and maintaining the data needed, and completing and reviewing the collection of information, Send comments regarding this burden estimate or any other aspect of this collection of information, including suggestions for reducing the burden, to the Department of Defense, Executive Services and Communications Directorate (07040188). Respondents should be aware that notwithstanding any other provision of law. no person shall be subject to any penalty for failing to comply with a collection of information if it does not display a currently valid OMB control number.
Optimal Yacht Rig Design
, 2010
"... If T is polyhedral (graph of T is a finite union of convex polyhedral sets) then PT is piecewise affine (continous, singlevalued, nonexpansive) (GE) is equivalent to 0 = F (PT (x)) + x − PT (x) and the “path following ” algorithm can be defined similarly to the variational inequality case. ..."
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If T is polyhedral (graph of T is a finite union of convex polyhedral sets) then PT is piecewise affine (continous, singlevalued, nonexpansive) (GE) is equivalent to 0 = F (PT (x)) + x − PT (x) and the “path following ” algorithm can be defined similarly to the variational inequality case.
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"... Optimization has evolved into a mature discipline over the past 60 or so years and can now be used to model and solve a host of problems arising in a variety of application areas. While the demonstrated value of optimization in solving standard models of increased size and complexity is of critical ..."
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Optimization has evolved into a mature discipline over the past 60 or so years and can now be used to model and solve a host of problems arising in a variety of application areas. While the demonstrated value of optimization in solving standard models of increased size and complexity is of critical importance, we firmly believe that the real value of optimization lies not in solving a single problem, but rather in providing insight and advice on the management of complex systems. Such advice needs to be part of an interactive debate with informed decision makers. An underused aspect of optimization models is as part of a process for finding “holes ” in a model—those features that an optimization code can quickly identify and exploit, but that are indicative of problems with the underlying model or analysis. We believe that optimization processes can be used to develop inputs for other parts of a solution (data processing); that strong optimization theory (of duality, for example) can enable more effective solution schemes that exploit model structure; and that the interplay between collections of models treating stochastic effects, competition between independent agents, and a mixture of continuous and discrete approaches can provide richness for describing, solving, and adapting the underlying system being modeled. Mechanisms that allow decision making in such circumstances can be informed by game theory and techniques from distributed computing. Exploiting these fundamental properties of an optimization system has the potential to influence many application domains in significant ways. To answer major design questions, small dynamic models need to be developed that are “level of detail ” specific; these models need to have interfaces to other “subservient ” models that provide appropriate aggregation of data and enhance overall understanding of the underlying complexities.