We describe in this paper a new approach to parallelize branch-and-bound on a certain number of processors. We propose to split the optimization of the original problem into the optimization of several subproblems that can be optimized separately with the goal that the amount of work that each processor carries out is balanced between the … Read more
Recent widespread interest in Convex Hull Pricing has not been accompanied by an equally broad understanding of the method. This paper seeks to narrow the gap between enthusiasm and comprehension. The connection between Convex Hull Pricing and basic electricity market clearing processes is clearly developed, and a new formulation of the pricing problem is presented. … Read more
The Swap Body Vehicle Routing Problem (SB-VRP) is a generalization of the classical Vehicle Routing Problem (VRP) where a particular structure as well as several operational aspects for the trucks composing the fleet are considered. This research has been motivated by the VeRoLog Solver Challenge 2014, organized together by VeRoLog and PTV group, aiming to … Read more
In this paper we address the Vehicle Routing Problem with Pickups and Deliveries (VRPPD), an extension of the classical Vehicle Routing Problem (VRP) where we consider precedences among customers, and develop an Integer Linear Programming (ILP) based local search procedure. We consider the capacitated one-to-one variant, where a particular precedence must be satisfied between pairs … Read more
We study same-day delivery (SDD) distribution systems by formulating the Dynamic Dispatch Wave Problem (DDWP), which models a depot where delivery requests arrive dynamically throughout a service day. At any dispatch epoch (wave), the information available to the decision maker is (1) a set of known, open requests which remain unfulfilled, and (2) a set … Read more
Recently, optimization problems involving nonsmooth and locally Lipschitz functions have been subject of investigation, and an innovative method known as Gradient Sampling has gained attention. Although the method has shown good results for important real problems, some drawbacks still remain unexplored. This study suggests modifications to the gradient sampling class of methods in order to … Read more
Although stochastic programming problems were always believed to be computationally challenging, this perception has only recently received a theoretical justification by the seminal work of Dyer and Stougie (Mathematical Programming A, 106(3):423–432, 2006). Amongst others, that paper argues that linear two-stage stochastic programs with fixed recourse are #P-hard even if the random problem data is … Read more
We begin by considering second order dynamical systems of the from $\ddot x(t) + \Gamma (\dot x(t)) + \lambda(t)B(x(t))=0$, where $\Gamma: {\cal H}\rightarrow{\cal H}$ is an elliptic bounded self-adjoint linear operator defined on a real Hilbert space ${\cal H}$, $B: {\cal H}\rightarrow{\cal H}$ is a cocoercive operator and $\lambda:[0,+\infty)\rightarrow [0,+\infty)$ is a relaxation function depending … Read more
It is known that the complementarity problems and the variational inequality problems are reformulated equivalently as a vector equation by using the natural residual or Fischer-Burmeister function. In this short paper, we first study the global convergence of a sequential injective algorithm for weakly univalent vector equation. Then, we apply the convergence analysis to the … Read more
The limited predictability and high variability of renewable generations has brought significant challenges on the real-time operation of bulk power systems. This paper proposes the concept of real-time dispatchability (RTDA) of power systems with variable energy resources, which focuses on investigating the impact of operating constraints and the cost of corrective actions on the flexibility … Read more