We derive closed-form solutions to optimal stopping problems related the pricing of perpetual American withdrawable standard and lookback put call options in an extension Black-Merton-Scholes model with asymmetric information. It is assumed that contracts are withdrawn by their writers at last hitting times for underlying risky asset price its running maximum or minimum over infinite time inter...

The paper is focussing on some recent developments in nonparametric mixture distributions. It discusses nonparametric maximum likelihood estimation of the mixing distribution and will emphasize gradient type results, especially in terms of global results and global convergence of algorithms such as vertex direction or vertex exchange method. However, the NPMLE (or the algorithms constructing it...

A new deterministic method for solving a global optimization problem is proposed. The proposed method consists of three phases. The first phase is a typical local search to compute a local minimum. The second phase employs a discrete sup-local search to locate a so-called sup-local minimum taking the lowest objective value among the neighboring local minima. The third phase is an attractor-base...

In this paper, an iterative optimization algorithm, called the Comb algorithm, is presented for approximating the global solution to MAP image restoration and segementation. The Comb derives new initial conngurations based on the best local minimum found so far and leads a local search towards the global minimum. Experimental comparisons show that the Comb produces solutions of quality comparab...

A variety of blind equalization algorithms exist. These algorithms, which draw on some theoretical justification for the demonstration or analysis of their purportedly ideal convergence properties, almost invariably rely on the input data being independent and identically distributed (i.i.d.). In contrast, in this paper we show that input correlation can have a marked effect on the character of...

Local linear M-smoothing is proposed as a method for noise reduction in one-dimensional (1D) signals. It is more appropriate than conventional local linear smoothing, because it does not introduce blurring of jumps in the signal. It improves local constant Msmoothing, by avoiding boundary effects at edges and jumps. While the idea of local linear M-smoothing is straightforward, numerical issues...

Given a graph G = (V, E), the independent set problem is that of finding a maximum-cardinality subset S of V such that no two vertices in S are adjacent. We present a fast local search routine for this problem. Our algorithm can determine in linear time if a maximal solution can be improved by replacing a single vertex with two others. We also show that an incremental version of this method can...

In this paper we present the problem of decision making on the facility location and pricing. We assume that the facilities can charge the different prices and the objective is to maximize the overall revenue. It is known that the problem is NPhard in the strong sense even for the given facility location. A two level local search heuristic based on the VNS framework is developed for this nonlin...