Feedback and time are essential for the optimal control of computing systems

The performance, reliability, cost, size and energy usage of computing systems can be improved by one or more orders of magnitude by the systematic use of modern control and optimization methods. Computing systems rely on the use of feedback algorithms to schedule tasks, data and resources, but the models that are used to design these algorithms are validated using open-loop metrics. By using closed-loop metrics instead, such as the gap metric developed in the control community, it should be possible to develop improved scheduling algorithms and computing systems that have not been over-engineered. Furthermore, scheduling problems are most naturally formulated as constraint satisfaction or mathematical optimization problems, but these are seldom implemented using state of the art numerical methods, nor do they explicitly take into account the fact that the scheduling problem itself takes time to solve. This paper makes the case that recent results in real-time model predictive control, where optimization problems are solved in order to control a process that evolves in time, are likely to form the basis of scheduling algorithms of the future. We therefore outline some of the research problems and opportunities that could arise by explicitly considering feedback and time when designing optimal scheduling algorithms for computing systems

Geometrically nonlinear analysis of the Apollo aft heat shield Final report, 1 Apr. 1966 - 15 Dec. 1966

Structural analysis of Apollo aft heat shield under water impact loading condition

Finding weakly reversible realizations of chemical reaction networks using optimization

An algorithm is given in this paper for the computation of dynamically equivalent weakly reversible realizations with the maximal number of reactions, for chemical reaction networks (CRNs) with mass action kinetics. The original problem statement can be traced back at least 30 years ago. The algorithm uses standard linear and mixed integer linear programming, and it is based on elementary graph theory and important former results on the dense realizations of CRNs. The proposed method is also capable of determining if no dynamically equivalent weakly reversible structure exists for a given reaction network with a previously fixed complex set.Comment: 18 pages, 9 figure

New directions in water resources management: The role of water pricing policies

Water resources will face increasing competition and higher environmental concerns during this century. To meet these challenges, the new Water Framework Directive has drawn up an integrated framework and established the basic principles for a sustainable water policy in the European Union. The introduction of water prices reflecting the true cost of irrigation is one of its most innovative components. In this paper, a positive mathematical programming model is developed to assess the environmental and socio-economic impacts of water pricing policies in Spanish irrigated lands. The model interface allows friendly use and easy replication in a large number of irrigation districts, selected throughout the Spanish territory. The model results show the impact on environmental indicators, water consumption, cropping patterns, technology adoption, labor, farmers' income, and the water agency revenues when different scenarios of cost recovery are considered. It is argued that this modeling approach may be used as a management tool to assist in the implementation of the cost recovery approach of the new Water Framework Directive

Necessary Optimality Conditions for Continuous-Time Optimization Problems with Equality and Inequality Constraints

The paper is devoted to obtain first and second order necessary optimality conditions for continuous-time optimization problems with equality and inequality constraints. A full rank type regularity condition along with an uniform implicit function theorem are used in order to establish such necessary conditions.Comment: 20 page