A variation of the P2P strategy, known as egalitarian P2P (E-P2P) refueling strategy, relaxes the restriction on the active satellites to return to their original orbital slots after undergoing the fuel transactions. The E-P2P refueling problem can be formulated as a three-index assignment problem on an undirected tripartite constellation graph, which can be solved using, say, a Greedy Random A...

We develop and implement a model for a profit maximizing firm that provides an intermediation service between commodity producers and commodity end-users distributed over a realistic spatial network. Producers and end-users trade with the firm through contracts for delivery of grain during the marketing season. The firm begins the marketing season with a portfolio of prearranged purchase and sa...

A new numerical method to calculate exact ground states of multifluxline systems with quenched disorder is presented, which is based on the minimum cost flow algorithm from combinatorial optimization. We discuss several models that can be studied with this method including their specific implementations, physically relevant observables and results: (1) The N-line model with N fluxlines (or dire...

Given an instance of the minimum cost flow problem, a version of the corresponding inverse problem, called the capacity inverse problem, is to modify the upper and lower bounds on arc flows as little as possible so that a given feasible flow x becomes optimal to the modified minimum cost flow problem. The modifications can be measured by different distances. Here, we consider the capacity inver...

We consider a class of learning problems that involve a structured sparsityinducing norm defined as the sum of l∞-norms over groups of variables. Whereas a lot of effort has been put in developing fast optimization methods when the groups are disjoint or embedded in a specific hierarchical structure, we address here the case of general overlapping groups. To this end, we show that the correspon...

The objective of the TanDEM-X Mission is the generation of a global high resolution Digital Elevation Model (DEM). To carry out this goal, two interferograms with different baselines will be acquired. We propose a novel two-stage multibaseline phase unwrapping method. Maximum Likelihood Estimation (MLE) is used to reduce the ambiguity and errors in gradient estimation on a pixel-by-pixel basis....

Identifying underlying structures in combinatorial optimisation problems leads to a better understanding of a problem and, consequently, to efficient solution methodologies. The present paper introduces a new network flow formulation for a large class of nurse rostering problems. By solving an integer minimum cost flow problem in a carefully constructed network, nurses’ shift schedules can be c...

In the Fixed Cost k-Flow problem, we are given a graph G = (V,E) with edge-capacities {ue | e ∈ E} and edge-costs {ce | e ∈ E}, source-sink pair s, t ∈ V , and an integer k. The goal is to find a minimum cost subgraph H of G such that the minimum capacity of an st-cut in H is at least k. We show that the Group Steiner on Trees problem is a special case of Fixed Cost k-Flow. This implies the fir...

This paper focuses on the resolution of the capacitated minimum cost flow problem on a network comprising n nodes and m arcs. We present a method that counts imperviousness to degeneracy among its strengths, namely the minimum mean cycle-canceling algorithm (MMCC). At each iteration, primal feasibility is maintained and the objective function strictly improves. The goal is to write a uniform an...

This paper presents two new scaling algorithms for the minimum cost network flow problem, one a primal cycle canceling algorithm, the other a dual cut canceling algorithm. Both algorithms scale a relaxed optimality parameter, and create a second, inner relaxation. The primal algorithm uses the inner relaxation to cancel a most negative node-disjoint family of cycles w.r.t. the scaled parameter,...