A Multistage Stochastic Programming Approach to the Dynamic and Stochastic VRPTW - Extended version

We consider a dynamic vehicle routing problem with time windows and stochastic customers (DS-VRPTW), such that customers may request for services as vehicles have already started their tours. To solve this problem, the goal is to provide a decision rule for choosing, at each time step, the next action to perform in light of known requests and probabilistic knowledge on requests likelihood. We introduce a new decision rule, called Global Stochastic Assessment (GSA) rule for the DS-VRPTW, and we compare it with existing decision rules, such as MSA. In particular, we show that GSA fully integrates nonanticipativity constraints so that it leads to better decisions in our stochastic context. We describe a new heuristic approach for efficiently approximating our GSA rule. We introduce a new waiting strategy. Experiments on dynamic and stochastic benchmarks, which include instances of different degrees of dynamism, show that not only our approach is competitive with state-of-the-art methods, but also enables to compute meaningful offline solutions to fully dynamic problems where absolutely no a priori customer request is provided.Comment: Extended version of the same-name study submitted for publication in conference CPAIOR201

A L\'evy input fluid queue with input and workload regulation

We consider a queuing model with the workload evolving between consecutive i.i.d.\ exponential timers $\{e_q^{(i)}\}_{i=1,2,...}$ according to a spectrally positive L\'evy process $Y_i(t)$ that is reflected at zero, and where the environment $i$ equals 0 or 1. When the exponential clock $e_q^{(i)}$ ends, the workload, as well as the L\'evy input process, are modified; this modification may depend on the current value of the workload, the maximum and the minimum workload observed during the previous cycle, and the environment $i$ of the L\'evy input process itself during the previous cycle. We analyse the steady-state workload distribution for this model. The main theme of the analysis is the systematic application of non-trivial functionals, derived within the framework of fluctuation theory of L\'evy processes, to workload and queuing models

Warehouse design and planning: A mathematical programming approach

The dynamic nature of today's competitive markets compels organizations to an incessant reassessment in an effort to respond to continuous challenges. Therefore, warehouses as an important link in most supply chains, must be continually re-evaluated to ensure that they are consistent with both market's demands and management's strategies. A number of warehouse decision support models have been proposed in the literature but considerable difficulties in applying these models still remain, due to the large amount of information to be processed and to the large number of possible alternatives. In this paper we discuss a mathematical programming model aiming to support some warehouse management and inventory decisions. In particular a large mixed-integer nonlinear programming model (MINLP) is presented to capture the trade-offs among the different inventory and warehouse costs in order to achieve global optimal design satisfying throughput requirements.(undefined)info:eu-repo/semantics/publishedVersio

Efficacy of the combination of cisplatin with either gemcitabine and vinorelbine or gemcitabine and paclitaxel in the treatment of locally advanced or metastatic non-small-cell lung cancer: a phase III randomised trial of the Southern Italy Cooperative Oncology Group (SICOG 0101)

Triplet regimens were occasionally reported to produce a higher response rate (RR) than doublets in locally advanced or metastatic non-small-cell lung cancer (NSCLC). This trial was conducted to assess (i) whether the addition of cisplatin (CDDP) to either gemcitabine (GEM) and vinorelbine (VNR) or GEM and paclitaxel (PTX) significantly prolongs overall survival (OS) and (ii) to compare the toxicity of PTX-containing and VNR-containing combinations

Constraint Propagation for the Dial-a-Ride Problem with Split Loads

International audienceAbstract. This paper deals with a new problem: the Dial and Ride Problem with Split Loads (DARPSL), while using randomized greedy insertion techniques together with constraint propagation techniques. Though it focuses here on the static versions of Dial and Ride, it takes into account the fact that practical DARP has to be handled according to a dynamical point of view, and even, in some case, in real time contexts. So, the kind of algorithmic solution which is proposed here, aim at making easier to bridge both points of view. First, we propose the general framework of the model and discuss the link with dynamical DARP, second, we describe the two algorithms (DARP and DARPSL), and lastly, show numerical experiments for both

Waste processing facility location problem by stochastic programming: Models and solutions

The paper deals with the so-called waste processing facility location problem (FLP), which asks for establishing a set of operational waste processing units, optimal against the total expected cost. We minimize the waste management (WM) expenditure of the waste producers, which is derived from the related waste processing, transportation, and investment costs. We use a stochastic programming approach in recognition of the inherent uncertainties in this area. Two relevant models are presented and discussed in the paper. Initially, we extend the common transportation network flow model with on-and-off waste-processing capacities in selected nodes, representing the facility location. Subsequently, we model the randomly-varying production of waste by a scenario-based two-stage stochastic integer linear program. Finally, we employ selected pricing ideas from revenue management to model the behavior of the waste producers, who we assume to be environmentally friendly. The modeling ideas are illustrated on an example of limited size solved in GAMS. Computations on larger instances were realized with traditional and heuristic algorithms, implemented within MATLAB. © Springer Nature Switzerland AG 2019

A general framework for active distribution network planning

The “Copernican revolution” from the current passive distribution system to the future Smart Grid paradigm aims at applying at distribution level techniques and solutions that have been used for decades in the transmission system. The future availability at this level of an integrated system for its operation is changing the planning objectives that will be mostly oriented to the maximum exploitation of existing assets and infrastructures, by working them much closer to their physical limits than in the past. The future distribution network planning will be defined with less network investments since operation’s issues can be fixed with the so called “no-network” solutions, like generator dispatch, demand side integration, control of transformer taps, reactive power management, and system reconfiguration. For these reasons, it is crucial that modern planning tools for the Active Distribution Networks integrate network operation practices in the set of feasible planning alternatives, in order to identify the best technical and economic balance between the innovative active management (that tends to maximize the utilization of existing assets in distribution network) and the traditional network expansion. The representation of load and generators cannot be based yet on unique yearly values as assumed until now by the traditional distribution planning tools, but there is the need of adopting time-series (or time dependent) models, in order to capture the operational aspects that can affect the planning stage. Obviously, for an accurate comparison of the planning options, the costs of the active management implementation should be defined, taking into account the dependency on the ICT and on the Regulatory environment (policy for refunding investments, obligation to serve or remuneration of the ancillary services). However, this evolution of the distribution network planning tools is not an easy task and many challenges arise that have to be faced. The paper presents the results of the activity conducted by the “Method for Active Network Planning” Task Force, part of the C6.19 working group, on this topic and proposes a general framework to be used as reference scheme for Active Distribution Network planning. Specifically, it is emphasised the need to apply probabilistic network calculations and risk assessments, to consider no-network solutions among the planning alternatives and to adopt Multi-Objective approaches

A New Monitor and Control Power Supply PCB for Biasing LNAs of Large Radio Telescopes Receivers

The biasing of low noise amplifiers (LNA) is of paramount importance for the receivers of large radio telescopes. High stability, optimal trade-off between gain and noise figure, remote control, and mitigation of the radio frequency interferences (RFIs) are all desirable features in the choice of the electronic board devoted to power supply the LNAs. In this paper, we propose the design and characterization of a multilayer printed circuit board (PCB), named GAIA, able to meet all the aforementioned requirements. The GAIA board is a 3-Unit, four-layer, rack-mountable, programmable PCB for the remote biasing of the LNAs, with monitor and control capabilities, specifically designed to operate in the receivers of the 64-m diameter Sardinia Radio Telescope (SRT). We describe the architecture, layout, and measurements of the GAIA board. Our results show that the GAIA power supply provides high stability of the output bias voltages and, in comparison with the old analogic biasing board used so far in the SRT receivers, it shows comparable or better frequency stability, other than a remarkable mitigation of the RFIs