New rate adaptation method for JPEG2000-based SNR Scalable Video Coding with Integer Linear Programming models

Abstract—In the last few years scalable video coding emerged as a promising technology for efficient distribution of videos through heterogeneous networks. In a heterogeneous environment, the video content needs to be adapted in order to meet different end terminal capability requirements (user adaptation) or fluctuations of the available bandwidth (network adaptation). Consequently, the adaptation problem is a critical issue in scalable video coding design. In this paper we introduce a new adaptation method for a proposed JPEG2000-based SNR scalable codec, that formulates and solves the adaptation problem as an Integer Linear Programming problem

Last Mile Delivery with Parcel Lockers: evaluating the environmental impact of eco-conscious consumer behavior

In recent months, online sales have experienced a sharp surge also due to the COVID pandemic. In this paper, we propose a new location and routing problem for a last mile delivery service based on parcel lockers and introduce a mathematical formulation to solve it by means of a MIP solver (Gurobi).The presence of parcel locker stations avoids the door-to-door delivery by companies but requires that consumers move from home to collect their parcels. Potential location of locker stations is known but not all of them need to be opened. The problem minimizes the global environmental impact in terms of distances traveled by both the delivery company and the consumers deciding the optimal number of stations that have to be opened.How much do the number and location of lockers impact on environment? Is the behavior of consumers a critical aspect of such optimization? To this aim we have solved 1680 instances and analyzed diferent scenarios varying the number of consumers and potential parcel lockers, the maximum distance a consumer is willing to travel to reach a locker station, and the maximum distance we may assume the same consumer is willing to travel by foot or by bicycle.The experimental results draw interesting conclusions and managerial insights providing important rules of thumbs for environmental decision makers.Copyright (c) 2022 The Authors. This is an open access article under the CC BY-NC-ND license (https://creativecommons.org/licenses/by-nc-nd/4.0/

Portfolio selection problems in practice: a comparison between linear and quadratic optimization models

Several portfolio selection models take into account practical limitations on the number of assets to include and on their weights in the portfolio. We present here a study of the Limited Asset Markowitz (LAM), of the Limited Asset Mean Absolute Deviation (LAMAD) and of the Limited Asset Conditional Value-at-Risk (LACVaR) models, where the assets are limited with the introduction of quantity and cardinality constraints. We propose a completely new approach for solving the LAM model, based on reformulation as a Standard Quadratic Program and on some recent theoretical results. With this approach we obtain optimal solutions both for some well-known financial data sets used by several other authors, and for some unsolved large size portfolio problems. We also test our method on five new data sets involving real-world capital market indices from major stock markets. Our computational experience shows that, rather unexpectedly, it is easier to solve the quadratic LAM model with our algorithm, than to solve the linear LACVaR and LAMAD models with CPLEX, one of the best commercial codes for mixed integer linear programming (MILP) problems. Finally, on the new data sets we have also compared, using out-of-sample analysis, the performance of the portfolios obtained by the Limited Asset models with the performance provided by the unconstrained models and with that of the official capital market indices

Comparison of policies in dynamic routing problems

We consider a company that has to satisfy customers' pick-up requests arriving over time every day. The overall objective of the company is to serve as many requests as possible at a minimum operational cost. When organizing its business the company has to fix some features of the service that may affect both service quality and operational costs. Some of these features concern the time a request is taken into account to plan its service, the associated deadline and the way requests are managed when the system is overloaded. In this paper we analyse several policies that can be implemented by the management of a carrier company in a multi-period context. For example, a company might reject all the requests that cannot be feasibly scheduled or accept all the requests and rely on a backup service in order to serve requests that are difficult to handle. Another interesting issue considered in this paper is the impact of collaborative service where two or more carrier companies, with their own customers, decide to share customers in order to optimize the overall costs. We set up a general framework to allow comparison of alternative service policies. Extensive computational results evaluating the number of lost requests and the distance travelled provide interesting insights

Local Search Algorithms for Portfolio Selection: Search Space and Correlation Analysis

Modern Portfolio Theory dates back from the fifties, and quantitative approaches to solve optimization problems stemming from this field have been proposed ever since. We propose a metaheuristic approach for the Portfolio Selection Problem that combines local search and Quadratic Programming, and we compare our approach with an exact solver. Search space and correlation analysis are performed to analyse the algorithm's performance, showing that metaheuristics can be efficiently used to determine optimal portfolio allocation

Processing second-order stochastic dominance models using cutting-plane representations

This is the post-print version of the Article. The official published version can be accessed from the links below. Copyright @ 2011 Springer-VerlagSecond-order stochastic dominance (SSD) is widely recognised as an important decision criterion in portfolio selection. Unfortunately, stochastic dominance models are known to be very demanding from a computational point of view. In this paper we consider two classes of models which use SSD as a choice criterion. The first, proposed by Dentcheva and Ruszczyński (J Bank Finance 30:433–451, 2006), uses a SSD constraint, which can be expressed as integrated chance constraints (ICCs). The second, proposed by Roman et al. (Math Program, Ser B 108:541–569, 2006) uses SSD through a multi-objective formulation with CVaR objectives. Cutting plane representations and algorithms were proposed by Klein Haneveld and Van der Vlerk (Comput Manage Sci 3:245–269, 2006) for ICCs, and by Künzi-Bay and Mayer (Comput Manage Sci 3:3–27, 2006) for CVaR minimization. These concepts are taken into consideration to propose representations and solution methods for the above class of SSD based models. We describe a cutting plane based solution algorithm and outline implementation details. A computational study is presented, which demonstrates the effectiveness and the scale-up properties of the solution algorithm, as applied to the SSD model of Roman et al. (Math Program, Ser B 108:541–569, 2006).This study was funded by OTKA, Hungarian National Fund for Scientific Research, project 47340; by Mobile Innovation Centre, Budapest University of Technology, project 2.2; Optirisk Systems, Uxbridge, UK and by BRIEF (Brunel University Research Innovation and Enterprise Fund)

inv(11)(q13q23)

Review on inv(11)(q13q23), with data on clinics, and the genes involved

Philosophy and the Integrity of the Person: The Phenomenology of Robert Sokolowski

This chapter offers an overview of the philosophy of Robert S. Sokolowski with a focus on his account of what philosophy is, how philosophy arises out of pre-philosophical life, and how it is related back to pre-philosophical life. It also situates Sokolowsk’s achievements in articulating the relationship between Husserlian phenomenology and modern and pre-modern styles of philosophizing

A Closed-Form Solution of the Multi-Period Portfolio Choice Problem for a Quadratic Utility Function

In the present paper, we derive a closed-form solution of the multi-period portfolio choice problem for a quadratic utility function with and without a riskless asset. All results are derived under weak conditions on the asset returns. No assumption on the correlation structure between different time points is needed and no assumption on the distribution is imposed. All expressions are presented in terms of the conditional mean vectors and the conditional covariance matrices. If the multivariate process of the asset returns is independent it is shown that in the case without a riskless asset the solution is presented as a sequence of optimal portfolio weights obtained by solving the single-period Markowitz optimization problem. The process dynamics are included only in the shape parameter of the utility function. If a riskless asset is present then the multi-period optimal portfolio weights are proportional to the single-period solutions multiplied by time-varying constants which are depending on the process dynamics. Remarkably, in the case of a portfolio selection with the tangency portfolio the multi-period solution coincides with the sequence of the simple-period solutions. Finally, we compare the suggested strategies with existing multi-period portfolio allocation methods for real data.Comment: 38 pages, 9 figures, 3 tables, changes: VAR(1)-CCC-GARCH(1,1) process dynamics and the analysis of increasing horizon are included in the simulation study, under revision in Annals of Operations Researc