We consider the classical Merton problem of lifetime consumption-portfolio optimization problem with small proportional transaction costs. The first order term in the asymptotic expansion is explicitly calculated through a singular ergodic control problem which can be solved in closed form in the one-dimensional case. Unlike the existing literature, we consider a general utility function and ge...

Refactoring is a well known technique to enhance various aspects of an object-oriented program. It has become very popular during recent years, as it allows to overcome deficits present in many programs. Doing refactoring by hand is almost impossible due to the size and complexity of modern software systems. Automated tools provide support for the application of refactorings, but do not give hi...

Recent comparative studies have demonstrated the usefulness of dependencybased contexts (DEPS) for learning distributed word representations for similarity tasks. In English, DEPS tend to perform better than the more common, less informed bag-of-words contexts (BOW). In this paper, we present the first crosslinguistic comparison of different context types for three different languages. DEPS are...

Linear programming duality yields e,cient algorithms for solving inverse linear programs. We show that special classes of conic programs admit a similar duality and, as a consequence, establish that the corresponding inverse programs are e,ciently solvable. We discuss applications of inverse conic programming in portfolio optimization and utility function identi0cation. c © 2004 Elsevier B.V. A...

We propose generalizations of the Global Cardinality Constraint (gcc) in which a partition of the variables is given. In the context of resource allocation problems, such constraints allow the expression of requirements, in terms of lower and upper bounds, for resources with different capabilities. Alternate models using gcc’s are shown to be weaker. We present filtering algorithms based on flo...

To solve the problem of heterogeneity of user requirements in grid resource allocation, a grid resource scheduling algorithm based on utility function is proposed by analyzing the relationship between the executing time and cost and the user utility function, the theory of economics is used to solve the optimal problem of the user utility function. The result of experiment shows, when the syste...

Program slicing is a well-known technique that has been widely used for debugging in the context of imperative programming. Debugging is a particularly difficult task within lazy declarative programming. In particular, there exist very few approaches to program slicing in this context. In this paper, we describe a slicing tool for firstorder lazy functional logic languages. We also illustrate i...

Abstract. This paper looks at the task of computing efficient extreme points in multiple objective linear programruing. Vector maximization software is reviewed and the ADBASE solver for computing all efficient extreme points of a multiple objective linear program is described. To create MOLP test problems, models for random problem generation are discussed. In the computational part of the pap...

UTA methods use linear programming techniques for finding additive utility functions that best explain stated preferences. However, most UTA methods including the popular UTA-Star are limited to monotonic preferences. UTA-NM (Non Monotonic) is inspired by UTA Star but allows non-monotonic partial utility functions if they decrease total model error. The shape of the utility functions is determi...

Human being is the most intelligent animal in this world. Intuitively, optimization algorithm inspired by human being creative problem solving process should be superior to the optimization algorithms inspired by collective behavior of insects like ants, bee, etc. In this paper, we introduce a novel brain storm optimization algorithm, which was inspired by the human brainstorming process. Two b...