Stochastic Vehicle Routing with Recourse

We study the classic Vehicle Routing Problem in the setting of stochastic optimization with recourse. StochVRP is a two-stage optimization problem, where demand is satisfied using two routes: fixed and recourse. The fixed route is computed using only a demand distribution. Then after observing the demand instantiations, a recourse route is computed -- but costs here become more expensive by a factor lambda. We present an O(log^2 n log(n lambda))-approximation algorithm for this stochastic routing problem, under arbitrary distributions. The main idea in this result is relating StochVRP to a special case of submodular orienteering, called knapsack rank-function orienteering. We also give a better approximation ratio for knapsack rank-function orienteering than what follows from prior work. Finally, we provide a Unique Games Conjecture based omega(1) hardness of approximation for StochVRP, even on star-like metrics on which our algorithm achieves a logarithmic approximation.Comment: 20 Pages, 1 figure Revision corrects the statement and proof of Theorem 1.

DOC 2015-03 Master of Finance

Legislative Authority. Constitution of the Academic Senate of the University of Dayton, Article ll.B.

Building Networks in the Face of Uncertainty

The subject of this thesis is to study approximation algorithms for some network design problems in face of uncertainty. We consider two widely studied models of handling uncertainties - Robust Optimization and Stochastic Optimization. We study a robust version of the well studied Uncapacitated Facility Location Problem (UFLP). In this version, once the set of facilities to be opened is decided, an adversary may close at most β facilities. The clients must then be assigned to the remaining open facilities. The performance of a solution is measured by the worst possible set of facilities that the adversary may close. We introduce a novel LP for the problem, and provide an LP rounding algorithm when all facilities have same opening costs. We also study the 2-stage Stochastic version of the Steiner Tree Problem. In this version, the set of terminals to be covered is not known in advance. Instead, a probability distribution over the possible sets of terminals is known. One is allowed to build a partial solution in the first stage a low cost, and when the exact scenario to be covered becomes known in the second stage, one is allowed to extend the solution by building a recourse network, albeit at higher cost. The aim is to construct a solution of low cost in expectation. We provide an LP rounding algorithm for this problem that beats the current best known LP rounding based approximation algorithm

A Review of Methodological Approaches for the Design and Optimization of Wind Farms

This article presents a review of the state of the art of the Wind Farm Design and Optimization (WFDO) problem. The WFDO problem refers to a set of advanced planning actions needed to extremize the performance of wind farms, which may be composed of a few individual Wind Turbines (WTs) up to thousands of WTs. The WFDO problem has been investigated in different scenarios, with substantial differences in main objectives, modelling assumptions, constraints, and numerical solution methods. The aim of this paper is: (1) to present an exhaustive survey of the literature covering the full span of the subject, an analysis of the state-of-the-art models describing the performance of wind farms as well as its extensions, and the numerical approaches used to solve the problem; (2) to provide an overview of the available knowledge and recent progress in the application of such strategies to real onshore and offshore wind farms; and (3) to propose a comprehensive agenda for future research

Functional module detection through integration of single-cell RNA sequencing data with protein–protein interaction networks

Funder: Novo Nordisk; doi: http://dx.doi.org/10.13039/501100004191Abstract: Background: Recent advances in single-cell RNA sequencing have allowed researchers to explore transcriptional function at a cellular level. In particular, single-cell RNA sequencing reveals that there exist clusters of cells with similar gene expression profiles, representing different transcriptional states. Results: In this study, we present scPPIN, a method for integrating single-cell RNA sequencing data with protein–protein interaction networks that detects active modules in cells of different transcriptional states. We achieve this by clustering RNA-sequencing data, identifying differentially expressed genes, constructing node-weighted protein–protein interaction networks, and finding the maximum-weight connected subgraphs with an exact Steiner-tree approach. As case studies, we investigate two RNA-sequencing data sets from human liver spheroids and human adipose tissue, respectively. With scPPIN we expand the output of differential expressed genes analysis with information from protein interactions. We find that different transcriptional states have different subnetworks of the protein–protein interaction networks significantly enriched which represent biological pathways. In these pathways, scPPIN identifies proteins that are not differentially expressed but have a crucial biological function (e.g., as receptors) and therefore reveals biology beyond a standard differential expressed gene analysis. Conclusions: The introduced scPPIN method can be used to systematically analyse differentially expressed genes in single-cell RNA sequencing data by integrating it with protein interaction data. The detected modules that characterise each cluster help to identify and hypothesise a biological function associated to those cells. Our analysis suggests the participation of unexpected proteins in these pathways that are undetectable from the single-cell RNA sequencing data alone. The techniques described here are applicable to other organisms and tissues

Corporate financial model for construction contractors

The prospect of business failure Is not a topic that most businesses care to acknowledge. However, in the construction industry failure Is a real possibility. The construction industry has several characteristics that sharply distinguish it from other sectors of the economy. The low level of working capital required to operate a contracting firm and the sensitivity of different sectors within the construction market to the economy are two of the most Important factors affecting the Industry. Previous attempts to identlfr and solve the problem of business failure concentrated upon the modification of contract regulations and did not receive considerable support. In the meantime, contractors should plan and control their activities in accordance with current environments and regulations. The Importance of cash flow forecasting is well emphasized In literature as current models failed to produce feasible and reliable tools. Being a large and well diversified organisation can be a good solution to the problems indicated above. The output of large construction companies is less sensitive to variations in the economy. The low level of working capital required to operate contracting activities Is balanced by other capital intensive businesses. The sensitivity of the construction company in general and the contracting division in particular to the fluctuations In individual contracts is limited. This is due to the large collateral available and the high number of contracts executed. Whilst maintaining all these advantages, large construction companies have failed to dominate a respectable share of the market against the high number of small and unstable contracting firms. Current practices with respect to corporate planning, financial planning and financial budgeting were examined in this research. A survey was undertaken for medium to large construction companies and findings confirmed that these practices were exercised inefficiently. Based on these findings, a corporate financial model was developed on a computer to assist medium to large construction divisions formulate and evaluate strategies. The model simulates strategies and environments and produces a comprehensive financial report which can then be used by contractors to control performance. The model generates construction output by integrating individual contracts. An Important part of the model Is the single net cash flow forecasting module. This module fulfilled other explicit applications for small as well as large contracting firms. The two models were evaluated through several tests and proved to be reliable. Current budgeting techniques were evaluated against the proposed model and were confirmed to be significantly incorrect. Contractors should not rely on their budgets and must use a model which is made to Incorporate variations In strategies and environments (i.e. the C.F.M.C.C.)