In this paper we present an iterative algorithm for the solution of regularization problems arising in inverse image processing. The regularization function to be minimized is constituted by two terms, a data fit function and a regularization function, weighted by a regularization parameter. The proposed algorithm solves the minimization problem and estimates the regularization parameter … Read more
The aim of operational train timetabling is to find a conflict free timetable for a set of passenger and freight trains with predefined stopping time windows along given routes in an infrastructure network so that station capacities and train dependent running and headway times are observed. Typical models for this problem are based on time-discretized … Read more
Kitahara and Mizuno get upper bounds for the maximum number of different basic feasible solutions generated by Dantzig�s simplex method. In this paper, we obtain lower bounds of the maximum number. Part of the results in this paper are shown in a paper by the authors as a quick report without proof. They present a … Read more
In this paper, we study the preferences for uncertain travel time in which the probability distribution may not be fully characterized. In evaluating an uncertain travel time, we explicitly distinguish between risk, where probability distribution is precisely known, and ambiguity, where it is not. In particular, we propose a new criterion called ambiguity-aware CARA travel … Read more
We consider a probabilistic set covering problem where there is uncertainty regarding whether a selected set can cover an item, and the objective is to determine a minimum-cost combination of sets so that each item is covered with a pre-specified probability. To date, literature on this problem has focused on the special case in which … Read more
We consider the problem of deleting a limited number of nodes from a graph in order to minimize a connectivity measure between the surviving nodes. We prove that the problem is $NP$-complete even on quite particular types of graph, and define a dynamic programming recursion that solves the problem in polynomial time when the graph … Read more
We propose a Newton method for solving smooth unconstrained vector optimization problems under partial orders induced by general closed convex pointed cones. The method extends the one proposed by Fliege, Grana Drummond and Svaiter for multicriteria, which in turn is an extension of the classical Newton method for scalar optimization. The steplength is chosen by … Read more
In this paper we deal with the critical node problem, where a given number of nodes has to be removed from an undirected graph in order to maximize the disconnections between the node pairs of the graph. We propose an integer linear programming model with a non-polynomial number of constraints but whose linear relaxation can … Read more
The Nelder-Mead algorithm, a longstanding direct search method for unconstrained optimization published in 1965, is designed to minimize a scalar-valued function $f$ of $n$ real variables using only function values, without any derivative information. Each Nelder–Mead iteration is associated with a nondegenerate simplex defined by $n + 1$ vertices and their function values; a typical … Read more
We study a mixed integer linear program with $m$ integer variables and $k$ non-negative continuous variables in the form of the relaxation of the corner polyhedron that was introduced by Andersen, Louveaux, Weismantel and Wolsey [\emph{Inequalities from two rows of a simplex tableau}, Proc.\ IPCO 2007, LNCS, vol.~4513, Springer, pp.~1–15]. We describe the facets of … Read more