A multicriteria decision aid approach for energy planning problems: The case of renewable energy option

In the past, the choice among alternative energy policies at regional level was based only on cost minimization. Lately, it is widely recognized that regional energy planning forms a multi-actor and multicriteria problem. This is particularly true in the case of power generation in regions presenting high rates of increase in electricity demand, together with a significant potential of renewable energy sources, since several and often conflicting points of view must be taken into account. In this paper, the contribution of a Multicriteria Decision Aid method — namely ELECTRE III — addressing in such problems is investigated through the examination of a particular case study in a Greek island. Through the presentation of the procedure followed (identification of actors, selection of criteria, formulation of alternative strategies, application of the specific method and analysis of results and actors' reactions), an effort is made to highlight those aspects that are crucial in reaching a compromise in regional energy planning problems.     

COMPARING PROACTIVE AND REACTIVE MANAGEMENT: MANAGING A TRANSBOUNDARY FISH STOCK UNDER CHANGING ENVIRONMENT

Environmental change in general, and climate change in particular, can lead to changes in distribution of fish stocks. When such changes involve transboundary fish stocks, the countries sharing the stock need to reconsider their harvesting policies. We investigate the effects of changing stock distribution on the optimal fishing policies in a two players’ noncooperative game. We compare reactive management, under which the manager ignores future distributional shifts (knowingly or unknowingly), with proactive management where the manager considers such shifts in his decisions. A dynamic programming model is developed to identify closed‐loop Nash strategies. We show that the role of two players is symmetric under reactive management but asymmetric under proactive management where managers anticipate future changes in stock ownership. The player losing the stock tends to harvest more aggressively compared to the player gaining the stock who acts more conservatively. Strategic interactions show tendency for complementary actions that can change abruptly during the ownership transition. The differences between management regimes vary from quantitative to qualitative; differences are minimal for stocks with little or no schooling, whereas highly schooling stocks may avoid collapse only under proactive management.     

Visualization of Multivariate Density Estimates With Level Set Trees

This article presents a method for visualization of multivariate functions. The method is based on a tree structure—called the level set tree—built from separated parts of level sets of a function. The method is applied for visualization of estimates of multivarate density functions. With different graphical representations of level set trees we may visualize the number and location of modes, excess masses associated with the modes, and certain shape characteristics of the estimate. Simulation examples are presented where projecting data to two dimensions does not help to reveal the modes of the density, but with the help of level set trees one may detect the modes. I argue that level set trees provide a useful method for exploratory data analysis.     

Reconstruction of Geophysical Layers with Shape Optimization and Level Set Methods

A shape optimization method is used to reconstruct the unknown shape of geophysical layers from boundary heat flux measurements by the use of adjoint fields and level sets. The identification of the shape of the geophysical layers by boundary heat flux measurements is necessary for the efficient use of geothermal energy. The method of speed is used to calculate the shape sensitivities, and the continuous adjoint approach is followed for the computation of the shape derivatives. The unknown shape is described with the help of the level set function; the advantage of the shape function is that no mesh movement or remeshing is necessary, but an additional Hamilton-Jacobi equation has to be solved. This equation is solved in an artificial time, where the velocity represents the movement in the direction of the normal vector of the interface. For large optimization steps, re-initialization of the level set function is also necessary, in order to keep the magnitude of the level set function near unity and also to smooth the level set function. Numerical results are given for measured heat fluxes on the boundary of the domain for different time steps and conductivity ratios. (© 2010 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim)     

The Minimal Requirements Approach to Policy Modelling in Public Planning

This paper argues that an approach to policy modelling in public planning must deal with the existence of conflicts between actors holding constraint sets, rather than players with strategies able to affect each other's payoffs. This approach builds on the policy level language proposed by Shiv K. Gupta and Laurence D. Richards. Operational definitions of modelling variables, conflict situations and potential pairwise coalitions are given. The approach is simple enough to allow manual calculation in small-scale problems and has a matrix notation which enables the use of computer programs for large-scale problems. A conceptual example which illustrates the features of the proposed modelling approach is presented and discussed.     

Following homology in singularly perturbed systems

The fast systems associated to a system of first-order equations where a small parameter multiplies the derivatives (hereinafter, an SPMD system) are obtained by stretching time by a factor of one over the small parameter and then reducing the small parameter to zero. Curves of isolated invariant sets associated to the fast system serve as approximate solutions to the SPMD system over finite intervals in the following sense: A manifold of initial points representing non-zero homology α in the Morse-Conley index of the invariant set at the left endpoint has a submanifold which is carried by the flow of the SPMD system to a manifold representing that non-zero homology class in the index of the invariant set at the right endpint which is the continuation of α along the curve of invariants sets. This is a type of linearization of the approximation problem since the continuation of homology classes along the curve of invariant sets is given by a linear transformation which varies functorially with the curve of invariant sets. Examples are given for systems in R² and R³. The results are used elsewhere to prove existence theorems for two point boundary value problems to obtain solutions with boundary and interior transition layers.     

Upper and Lower Hausdorff Dimension Estimates for Invariant Sets of k — 1 — Endomorphisms

For a special class of non–injective maps on Riemannian manifolds upper and lower bounds for the Hausdorff dimension of invariant sets are given in terms of the singular values of the tangent map. The upper estimation is based on a theorem by Douady and Oesterlé and its generalization to Riemannian manifolds by Noack and Reitmann , but additionally information about the noninjectivity is used. The lower estimation can be reached by modifying a method, derived by Shereshevskij for geometric constructions on the real line (also described by Barreira , for similar constructions in general metric spaces. The upper and lower dimension estimates for k — 1 — endomorphisms can for instance be applied to Julia sets of quadratic maps on the complex plane.     

Finding near-optimal independent sets at scale

The maximum independent set problem is NP-hard and particularly difficult to solve in sparse graphs, which typically take exponential time to solve exactly using the best-known exact algorithms. In this paper, we present two new novel heuristic algorithms for computing large independent sets on huge sparse graphs, which are intractable in practice. First, we develop an advanced evolutionary algorithm that uses fast graph partitioning with local search algorithms to implement efficient combine operations that exchange whole blocks of given independent sets. Though the evolutionary algorithm itself is highly competitive with existing heuristic algorithms on large social networks, we further show that it can be effectively used as an oracle to guess vertices that are likely to be in large independent sets. We then show how to combine these guesses with kernelization techniques in a branch-and-reduce-like algorithm to compute high-quality independent sets quickly in huge complex networks. Our experiments against a recent (and fast) exact algorithm for large sparse graphs show that our technique always computes an optimal solution when the exact solution is known, and it further computes consistent results on even larger instances where the solution is unknown. Ultimately, we show that identifying and removing vertices likely to be in large independent sets opens up the reduction space—which not only speeds up the computation of large independent sets drastically, but also enables us to compute high-quality independent sets on much larger instances than previously reported in the literature.     

On the convergence of the DFP algorithm for unconstrained optimization when there are only two variables

Let the DFP algorithm for unconstrained optimization be applied to an objective function that has continuous second derivatives and bounded level sets, where each line search finds the first local minimum. It is proved that the calculated gradients are not bounded away from zero if there are only two variables. The new feature of this work is that there is no need for the objective function to be convex. Received: June 16, 1999 / Accepted: December 24, 1999?Published online March 15, 2000     

Stabilizing employment in a fluctuating resource economy

We consider a resource management problem in which the management objective is to minimize fluctuations in resource economics. Stabilizing management policies consist of memoryless state feedback control strategies for a class of discrete-time resource models which contain unknown but bounded fluctuations. The underlying theory is based on conditions developed for Lyapunov-type stability of sets. The design of the stabilizing policies is illustrated by a simulation example from resource economics. Specifically, employment of fishermen is stabilized by using a subsidizing and taxing policy in an open-access common-property fishery in which the value of the resource and the resource level fluctuate, and where entry and exit dynamics are determined by fluctuating revenues obtained from the fishery.This work was supported by NSF and AFOSR under Grant No. ECS-86-02524.The support by the Yrjö Jahnsson Foundation is greatly acknowledged.     

A note on DOL length sets

Length sets of polynomially bounded DOL systems are considered by analyzing sets K ∩ {n : n ? q} where K is a DOL length set. It turns out that DOL and PDOL systems behave in different ways with respect to these sets. Especially, it follows that all DOL length sets— contrary to PDOL length sets—are not generated unambiguously, i.e. without repetitions, by DOL systems. Moreover it is proved that the number of axioms used determines an infinite hierarchy of length set families both in DOL and PDOL case.     

Conceptions of Science Achievement in Major Reform Documents

The construct of science achievement—what K‐12 students should know and be able to do in science—is central to science education reform. This paper examines current conceptions of science achievement in major reform documents in the context of standards‐based and systemic reform. The paper reviews documents on (a) science content standards, including the National Science Education Standards ( National Research Council, 1996 ) and Project 2061 ( American Association for the Advancement of Science, 1989, 1993 ); (b) performance standards in the New Standards Project ( National Center on Education and the Economy, 1997a, 1997b, 1997c, 1998 ); and (c) assessment frameworks, including the 1996 National Assessment of Educational Progress ( National Assessment Governing Board, 1994, 1996 ) and the Third International Mathematics and Science Study ( Martin & Kelly, 1996 ; McKnight, Schmidt, & Raizen, 1993 ; Robitallie et al., 1993 ). Although there is an overall agreement on the conceptions of science achievement among the documents, there are also noticeable differences. Based on the analysis of the five sets of documents, an aggregated view of science achievement is presented in terms of science content and process. Implications for promoting science achievement in standards‐based and systemic reform are discussed.     

Locating flow-capturing units on a network with multi-counting and diminishing returns to scale

In the paper we consider the problem of locating flow-capturing units (facilities) on a transportation network, where the level of consuming service by customers depends on the number of facilities that they encounter on their pre-planned tour (the effect of multi-counting). Two location problems are considered: Problem 1 — minimizing the number of facilities required to ensure the maximal level of consumption, and Problem 2 — maximizing the total consumption given a restriction on the number of facilities. Both problems are NP-hard on general networks. Integer programming formulations of the problems are given. For Problem 2, a heuristic with worst-case analysis is presented. It is shown that Problem 2 is NP-hard even on a tree (and even without multi-counting). For Problem 1 on a tree a polynomial algorithm is presented. If it is required additionally that at most one facility can be located at each node and locations are restricted to nodes, then both problems are NP-hard on trees.     

On the optimal control of partially observed inventory systems

This Note introduces recent developments in the analysis of inventory systems with partial observations. The states of these systems are typically conditional distributions, which evolve in infinite dimensional spaces over time. Our analysis involves introducing unnormalized probabilities to transform nonlinear state transition equations to linear ones. With the linear equations, the existence of the optimal feedback policies are proved for two models where demand and inventory are partially observed. In a third model where the current inventory is not observed but a past inventory level is fully observed, a sufficient statistic is provided to serve as a state. The last model serves as an example where a partially observed model has a finite dimensional state. In that model, we also establish the optimality of the basestock policies, hence generalizing the corresponding classical models with full information. To cite this article: A. Bensoussan et al., C. R. Acad. Sci. Paris, Ser. I 341 (2005).     

近似函数高阶导数的高精度积分逼近方法

主要研究稳定计算近似函数的高阶导数的积分逼近方法,方法因由Lanczos提出故也称为Lanczos算法.利用Legendre多项式的正交性,提出了一类逼近近似函数高阶导数的高精度积分方法,即构造出一系列积分算子Dn,h(m)去逼近噪声函数的高阶导数,且这些积分算子具有O(δ(2n+2)/(2n+m+2))的收敛速度,其中δ为近似函数的噪声水平.数值模拟结果表明提出的方法是稳定而有效的.     

Concurrency and Commitment: Network Scheduling and Its Consequences for Diffusion 1

Network ties are thought to be concurrent—one can “have” many friends at once, for instance—but their concrete enactment is largely serial and episodic, guided by priorities that steer a person from one encounter to the next. Further, dyadic encounters require that two people be simultaneously available to interact, creating the need for coordinated scheduling. Here I study the consequences of scheduling for network diffusion, using a computer simulation that interposes a scheduling process between a pre-existing network and instances of contagion. The pace and extent of diffusion are shown to depend upon the interaction of network topology, contagion rule (on first-contact versus at some threshold), and whether actors try to remedy past scheduling imperfections. Scheduling turns central actors into diffusion bottlenecks, but can also trigger early adoption by giving actors false readings on the status of their network alters. The implications of scheduling extend beyond diffusion, to other outcomes such as decision-making, as well as to network evolution.