Variable Neighborhood Search for Solving the Capacitated Single Allocation Hub Location Problem

In this paper a Variable Neighborhood Search (VNS) algorithm for solving the Capacitated Single Allocation Hub Location Problem (CSAHLP) is presented. CSAHLP consists of two subproblems; the first is choosing a set of hubs from all nodes in a network, while the other comprises finding the optimal allocation of non-hubs to hubs when a set of hubs is already known. The VNS algorithm was used for the first subproblem, while the CPLEX solver was used for the second. Computational results demonstrate that the proposed algorithm has reached optimal solutions on all 20 test instances for which optimal solutions are known, and this in short computational time.

Wealth shocks, credit-supply shocks, and asset allocation:evidence from household and firm portfolios

We use a unique dataset with bank clients’ security holdings for all German banks to examine how macroeconomic shocks affect asset allocation preferences of households and non-financial firms. Our analysis focuses on two alternative mechanisms which can influence portfolio choice: wealth shocks, which are represented by the sovereign debt crisis in the Eurozone, and credit-supply shocks which arise from reductions in borrowing abilities during bank distress. We document het- erogeneous responses to these two types of shocks. While households with large holdings of secu- rities from stressed Eurozone countries (Greece, Ireland, Italy, Portugal, and Spain) decrease the degree of concentration in their security portfolio as a result of the Eurozone crisis, non-financial firms with similar levels of holdings from stressed Eurozone countries do not. Credit-supply shocks at the bank level (caused by bank distress) result in lower concentration, for both households and non-financial corporations. We also show that only shocks to corporate credit bear ramifications on bank clients’ portfolio concentration, while shocks in retail credit are inconsequential. Our results are robust to falsification tests, propensity score matching techniques, and instrumental variables estimation.

Message passing for distributed optimisation of power allocation with renewable resources

The increase in renewable energy generators introduced into the electricity grid is putting pressure on its stability and management as predictions of renewable energy sources cannot be accurate or fully controlled. This, with the additional pressure of fluctuations in demand, presents a problem more complex than the current methods of controlling electricity distribution were designed for. A global approximate and distributed optimisation method for power allocation that accommodates uncertainties and volatility is suggested and analysed. It is based on a probabilistic method known as message passing [1], which has deep links to statistical physics methodology. This principled method of optimisation is based on local calculations and inherently accommodates uncertainties; it is of modest computational complexity and provides good approximate solutions.We consider uncertainty and fluctuations drawn from a Gaussian distribution and incorporate them into the message-passing algorithm. We see the effect that increasing uncertainty has on the transmission cost and how the placement of volatile nodes within a grid, such as renewable generators or consumers, effects it.

Numerical solution of the Dirichlet initial boundary value problem for the heat equation in exterior 3-dimensional domains using integral equations

A numerical method for the Dirichlet initial boundary value problem for the heat equation in the exterior and unbounded region of a smooth closed simply connected 3-dimensional domain is proposed and investigated. This method is based on a combination of a Laguerre transformation with respect to the time variable and an integral equation approach in the spatial variables. Using the Laguerre transformation in time reduces the parabolic problem to a sequence of stationary elliptic problems which are solved by a boundary layer approach giving a sequence of boundary integral equations of the first kind to solve. Under the assumption that the boundary surface of the solution domain has a one-to-one mapping onto the unit sphere, these integral equations are transformed and rewritten over this sphere. The numerical discretisation and solution are obtained by a discrete projection method involving spherical harmonic functions. Numerical results are included.

Semi-supervised Gaussian process latent variable model with pairwise constraints

In machine learning, Gaussian process latent variable model (GP-LVM) has been extensively applied in the field of unsupervised dimensionality reduction. When some supervised information, e.g., pairwise constraints or labels of the data, is available, the traditional GP-LVM cannot directly utilize such supervised information to improve the performance of dimensionality reduction. In this case, it is necessary to modify the traditional GP-LVM to make it capable of handing the supervised or semi-supervised learning tasks. For this purpose, we propose a new semi-supervised GP-LVM framework under the pairwise constraints. Through transferring the pairwise constraints in the observed space to the latent space, the constrained priori information on the latent variables can be obtained. Under this constrained priori, the latent variables are optimized by the maximum a posteriori (MAP) algorithm. The effectiveness of the proposed algorithm is demonstrated with experiments on a variety of data sets. © 2010 Elsevier B.V.

A multi-organisational approach for disaster preparedness and response:the use of optimisation and GIS for facility location, stock pre-positioning, resource allocation and relief distribution

From 1992 to 2012 4.4 billion people were affected by disasters with almost 2 trillion USD in damages and 1.3 million people killed worldwide. The increasing threat of disasters stresses the need to provide solutions for the challenges faced by disaster managers, such as the logistical deployment of resources required to provide relief to victims. The location of emergency facilities, stock prepositioning, evacuation, inventory management, resource allocation, and relief distribution have been identified to directly impact the relief provided to victims during the disaster. Managing appropriately these factors is critical to reduce suffering. Disaster management commonly attracts several organisations working alongside each other and sharing resources to cope with the emergency. Coordinating these agencies is a complex task but there is little research considering multiple organisations, and none actually optimising the number of actors required to avoid shortages and convergence. The aim of the this research is to develop a system for disaster management based on a combination of optimisation techniques and geographical information systems (GIS) to aid multi-organisational decision-making. An integrated decision system was created comprising a cartographic model implemented in GIS to discard floodable facilities, combined with two models focused on optimising the decisions regarding location of emergency facilities, stock prepositioning, the allocation of resources and relief distribution, along with the number of actors required to perform these activities. Three in-depth case studies in Mexico were studied gathering information from different organisations. The cartographic model proved to reduce the risk to select unsuitable facilities. The preparedness and response models showed the capacity to optimise the decisions and the number of organisations required for logistical activities, pointing towards an excess of actors involved in all cases. The system as a whole demonstrated its capacity to provide integrated support for disaster preparedness and response, along with the existence of room for improvement for Mexican organisations in flood management.

Aid Allocation of the Emerging Central and Eastern European Donors

The paper examines the main characteristics of the (re)emerging foreign aid policies of the Visegrád countries (the Czech Republic, Hungary, Poland, Slovakia), concentrating on the allocation of their aid resources. We adopt an econometric approach, similar to the ones used in the literature for analyzing the aid allocation of the OECD DAC donors. Using this approach, we examine the various factors that influence aid allocation of the Visegrád countries, using data for the years between 2001 and 2008. Our most important conclusion is that the amount of aid a partner county gets from the four emerging donors is not influenced by the level of poverty or the previous performance (measured by the level of economic growth or the quality of institutions) of the recipients. The main determining factor seems to be geographic proximity, as countries in the Western-Balkans and the Post-Soviet region receive much more aid from the Visegrád countries than other recipients. Historical ties (pre-1989 development relations) and international obligations in the case of Afghanistan and Iraq are also found to be significant explanatory factors. This allocation is in line with the foreign political and economic interests of these new donors. While there are clear similarities between the four donors, the paper also identifies some individual country characteristics.

Tőkeallokációs módszerek és tulajdonságaik a gyakorlatban (Methods of capital allocation and their characteristics in practice)

A pénzügyekben mind elméletileg, mind az alkalmazások szempontjából fontos kérdés a tőkeallokáció. Hogyan osszuk szét egy adott portfólió kockázatát annak alportfóliói között? Miként tartalékoljunk tőkét a fennálló kockázatok fedezetére, és a tartalékokat hogyan rendeljük az üzleti egységekhez? A tőkeallokáció vizsgálatára axiomatikus megközelítést alkalmazunk, tehát alapvető tulajdonságok megkövetelésével dolgozunk. Cikkünk kiindulópontja Csóka-Pintér [2010] azon eredménye, hogy a koherens kockázati mértékek axiómái, valamint a tőkeallokációra vonatkozó méltányossági, ösztönzési és stabilitási követelmények nincsenek összhangban egymással. Ebben a cikkben analitikus és szimulációs eszközökkel vizsgáljuk ezeket a követelményeket. A gyakorlati alkalmazások során használt, illetve az elméleti szempontból érdekes tőkeallokációs módszereket is elemezzük. A cikk fő következtetése, hogy a Csóka-Pintér [2010] által felvetett probléma gyakorlati szempontból is releváns, tehát az nemcsak az elméleti vizsgálatok során merül fel, hanem igen sokszor előforduló és gyakorlati probléma. A cikk további eredménye, hogy a vizsgált tőkeallokációs módszerek jellemzésével segítséget nyújt az alkalmazóknak a különböző módszerek közötti választáshoz. / === / Risk capital allocation in finance is important theoretically and also in practical applications. How can the risk of a portfolio be shared among its sub-portfolios? How should the capital reserves be set to cover risks, and how should the reserves be assigned to the business units? The study uses an axiomatic approach to analyse risk capital allocation, by working with requiring basic properties. The starting point is a 2010 study by Csoka and Pinter (2010), who showed that the axioms of coherent measures of risk are not compatible with some fairness, incentive compatibility and stability requirements of risk allocation. This paper discusses these requirements using analytical and simulation tools. It analyses methods used in practical applications that have theoretically interesting properties. The main conclusion is that the problems identified in Csoka and Pinter (2010) remain relevant in practical applications, so that it is not just a theoretical issue, it is a common practical problem. A further contribution is made because analysis of risk allocation methods helps practitioners choose among the different methods available.

Aid Allocation of the Emerging Central and Eastern European Donors

The paper examines the main characteristics of the (re)emerging foreign aid policies of the Visegrád countries (the Czech Republic, Hungary, Poland, Slovakia), concentrating on the allocation of their aid resources. We adopt an econometric approach, similar to the ones used in the literature for analyzing the aid allocation of the OECD DAC donors. Using this approach, we examine the various factors that influence aid allocation of the Visegrád countries, using data for the years between 2001 and 2008. Our most important conclusion is that the amount of aid a partner county gets from the four emerging donors is not influenced by the level of poverty or the previous performance (measured by the level of economic growth or the quality of institutions) of the recipients. The main determining factor seems to be geographic proximity, as countries in the Western-Balkans and the Post-Soviet region receive much more aid from the Visegrád countries than other recipients. Historical ties (pre-1989 development relations) and international obligations in the case of Afghanistan and Iraq are also found to be significant explanatory factors. This allocation is in line with the foreign political and economic interests of these new donors. While there are clear similarities between the four donors, the paper also identifies some individual country characteristics.

On the impossibility of fair risk allocation

Measuring and allocating risk properly are crucial for performance evaluation and internal capital allocation of portfolios held by banks, insurance companies, investment funds and other entities subject to financial risk. We show that by using a coherent measure of risk it is impossible to allocate risk satisfying the natural requirements of (Solution) Core Compatibility, Equal Treatment Property and Strong Monotonicity. To obtain the result we characterize the Shapley value on the class of totally balanced games and also on the class of exact games.