1,007 research outputs found
Genetic embedded matching approach to ground states in continuous-spin systems
Due to an extremely rugged structure of the free energy landscape, the
determination of spin-glass ground states is among the hardest known
optimization problems, found to be NP-hard in the most general case. Owing to
the specific structure of local (free) energy minima, general-purpose
optimization strategies perform relatively poorly on these problems, and a
number of specially tailored optimization techniques have been developed in
particular for the Ising spin glass and similar discrete systems. Here, an
efficient optimization heuristic for the much less discussed case of continuous
spins is introduced, based on the combination of an embedding of Ising spins
into the continuous rotators and an appropriate variant of a genetic algorithm.
Statistical techniques for insuring high reliability in finding (numerically)
exact ground states are discussed, and the method is benchmarked against the
simulated annealing approach.Comment: 17 pages, 12 figures, 1 tabl
Working Notes from the 1992 AAAI Spring Symposium on Practical Approaches to Scheduling and Planning
The symposium presented issues involved in the development of scheduling systems that can deal with resource and time limitations. To qualify, a system must be implemented and tested to some degree on non-trivial problems (ideally, on real-world problems). However, a system need not be fully deployed to qualify. Systems that schedule actions in terms of metric time constraints typically represent and reason about an external numeric clock or calendar and can be contrasted with those systems that represent time purely symbolically. The following topics are discussed: integrating planning and scheduling; integrating symbolic goals and numerical utilities; managing uncertainty; incremental rescheduling; managing limited computation time; anytime scheduling and planning algorithms, systems; dependency analysis and schedule reuse; management of schedule and plan execution; and incorporation of discrete event techniques
Spatial Interactions of Peers and Performance of File Sharing Systems
We propose a new model for peer-to-peer networking which takes the network
bottlenecks into account beyond the access. This model allows one to cope with
key features of P2P networking like degree or locality constraints or the fact
that distant peers often have a smaller rate than nearby peers. We show that
the spatial point process describing peers in their steady state then exhibits
an interesting repulsion phenomenon. We analyze two asymptotic regimes of the
peer-to-peer network: the fluid regime and the hard--core regime. We get closed
form expressions for the mean (and in some cases the law) of the peer latency
and the download rate obtained by a peer as well as for the spatial density of
peers in the steady state of each regime, as well as an accurate approximation
that holds for all regimes. The analytical results are based on a mix of
mathematical analysis and dimensional analysis and have important design
implications. The first of them is the existence of a setting where the
equilibrium mean latency is a decreasing function of the load, a phenomenon
that we call super-scalability.Comment: No. RR-7713 (2012
The random K-satisfiability problem: from an analytic solution to an efficient algorithm
We study the problem of satisfiability of randomly chosen clauses, each with
K Boolean variables. Using the cavity method at zero temperature, we find the
phase diagram for the K=3 case. We show the existence of an intermediate phase
in the satisfiable region, where the proliferation of metastable states is at
the origin of the slowdown of search algorithms. The fundamental order
parameter introduced in the cavity method, which consists of surveys of local
magnetic fields in the various possible states of the system, can be computed
for one given sample. These surveys can be used to invent new types of
algorithms for solving hard combinatorial optimizations problems. One such
algorithm is shown here for the 3-sat problem, with very good performances.Comment: 38 pages, 13 figures; corrected typo
Quadratic Regularization of Unit-Demand Envy-Free Pricing Problems and Application to Electricity Markets
We consider a profit-maximizing model for pricing contracts as an extension
of the unit-demand envy-free pricing problem: customers aim to choose a
contract maximizing their utility based on a reservation bill and multiple
price coefficients (attributes). A classical approach supposes that the
customers have deterministic utilities; then, the response of each customer is
highly sensitive to price since it concentrates on the best offer. A second
approach is to consider logit model to add a probabilistic behavior in the
customers' choices. To circumvent the intrinsic instability of the former and
the resolution difficulties of the latter, we introduce a quadratically
regularized model of customer's response, which leads to a quadratic program
under complementarity constraints (QPCC). This allows to robustify the
deterministic model, while keeping a strong geometrical structure. In
particular, we show that the customer's response is governed by a polyhedral
complex, in which every polyhedral cell determines a set of contracts which is
effectively chosen. Moreover, the deterministic model is recovered as a limit
case of the regularized one. We exploit these geometrical properties to develop
an efficient pivoting heuristic, which we compare with implicit or non-linear
methods from bilevel programming. These results are illustrated by an
application to the optimal pricing of electricity contracts on the French
market.Comment: 37 pages, 9 figures; adding a section on the pricing of electricity
contract
Decision making and problem solving with computer assistance
In modern guidance and control systems, the human as manager, supervisor, decision maker, problem solver and trouble shooter, often has to cope with a marginal mental workload. To improve this situation, computers should be used to reduce the operator from mental stress. This should not solely be done by increased automation, but by a reasonable sharing of tasks in a human-computer team, where the computer supports the human intelligence. Recent developments in this area are summarized. It is shown that interactive support of operator by intelligent computer is feasible during information evaluation, decision making and problem solving. The applied artificial intelligence algorithms comprehend pattern recognition and classification, adaptation and machine learning as well as dynamic and heuristic programming. Elementary examples are presented to explain basic principles
Locating and Protecting Facilities Subject to Random Disruptions and Attacks
Recent events such as the 2011 Tohoku earthquake and tsunami in Japan have revealed the vulnerability of networks such as supply chains to disruptive events. In particular, it has become apparent that the failure of a few elements of an infrastructure system can cause a system-wide disruption. Thus, it is important to learn more about which elements of infrastructure systems are most critical and how to protect an infrastructure system from the effects of a disruption. This dissertation seeks to enhance the understanding of how to design and protect networked infrastructure systems from disruptions by developing new mathematical models and solution techniques and using them to help decision-makers by discovering new decision-making insights.
Several gaps exist in the body of knowledge concerning how to design and protect networks that are subject to disruptions. First, there is a lack of insights on how to make equitable decisions related to designing networks subject to disruptions. This is important in public-sector decision-making where it is important to generate solutions that are equitable across multiple stakeholders. Second, there is a lack of models that integrate system design and system protection decisions. These models are needed so that we can understand the benefit of integrating design and protection decisions. Finally, most of the literature makes several key assumptions: 1) protection of infrastructure elements is perfect, 2) an element is either fully protected or fully unprotected, and 3) after a disruption facilities are either completely operational or completely failed. While these may be reasonable assumptions in some contexts, there may exist contexts in which these assumptions are limiting. There are several difficulties with filling these gaps in the literature. This dissertation describes the discovery of mathematical formulations needed to fill these gaps as well as the identification of appropriate solution strategies
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