The Steiner Travelling Salesman Problem (STSP) is a variant of the TSP that is suitable for instances defined on road networks. We consider an extension of the STSP in which the road traversal costs are both stochastic and correlated. This happens, for example, when vehicles are prone to delays...

The Standard Quadratic Problem (StQP) is an NP-hard problem with many local minimizers (stationary points). In the literature, heuristics based on unconstrained continuous non-convex formulations have been proposed (Bomze & Palagi, 2005; Bomze, Grippo, & Palagi, 2012) but none dominates the other in...

This paper describes a limited-memory quasi-Newton method in which the initial inverse Hessian approximation is constructed based on the concept of equilibration of the inverse Hessian matrix. Curvature information about the objective function is stored in the form of a diagonal matrix, and...

In this article we survey mathematical programming approaches to problems in the field of drinking water distribution network optimization. Among the predominant topics treated in the literature, we focus on two different, but related problem classes. One can be described by the notion of...

In humans, the relationship between experience and productivity, also known as learning (possibly also including forgetting), is non-linear. As a result, prescriptive planning models that seek to manage workforce development through task assignment are difficult to solve. To overcome this...

We propose the problem of profit-based container assignment (P-CA), in which the container shipment demand is dependent on the freight rate, similar to the “elastic demand” in the literature on urban transportation networks. The problem involves determining the optimal freight rates, the...

<Para ID="Par1">Clustering is an important problem in data mining. It can be formulated as a nonsmooth, nonconvex optimization problem. For the most global optimization techniques this problem is challenging even in medium size data sets. In this paper, we propose an approach that allows one to apply local...</para>

A trust-region-based derivative free algorithm for solving bound constrained mixed integer nonlinear programs is developed in this paper. The algorithm is proven to converge to a local minimum after a finite number of function evaluations. In addition, an improved definition of local minima of...