Paths in remnant movement: A single solution to three problems in the Polish OVS syntax

On the one hand it has been advanced that remnant movement (RM) serves as a replacement for head movement and leads to certain permutations in word order while it disallows some others (e.g. Cinque (2005)), on the other hand, little attention has been devoted to the consequences RM has for clausal syntax. In this work, I illustrate one such consequence, namely the rise of crossing and nesting movement dependencies and their reflexes. In particular, I make a case for the existence of massive RM that involves entire clausal subtrees in Polish. The analysis provides a uniform solution to three robust puzzles in the Polish OVS construction in a straightforward way.

Nested Rollout Policy Adaptation for optimizing vehicle selection in complex VRPs

The goal of Vehicle Routing Problems (VRP) and their variations is to transport a set of orders with the minimum number of vehicles at least cost. Most approaches are designed to solve specific problem variations independently, whereas in real world applications, different constraints are handled concurrently. This research extends solutions obtained for the traveling salesman problem with time windows to a much wider class of route planning problems in logistics. The work describes a novel approach that:  supports a heterogeneous fleet of vehicles  dynamically reduces the number of vehicles  respects individual capacity restrictions  satisfies pickup and delivery constraints  takes Hamiltonian paths (rather than cycles) The proposed approach uses Monte-Carlo Tree Search and in particular Nested Rollout Policy Adaptation. For the evaluation of the work, real data from the industry was obtained and tested and the results are reported.

Equilibrium Assignments in Competitive and Cooperative Traffic Flow Routing

Part 18: Optimization in Collaborative Networks

Vehicle Routing Problems that Minimize the Completion Time: Heuristics, Worst-Case Analyses, and Computational Results

In the standard Vehicle Routing Problem (VRP), we route a fleet of vehicles to deliver the demands of all customers such that the total distance traveled by the fleet is minimized. In this dissertation, we study variants of the VRP that minimize the completion time, i.e., we minimize the distance of the longest route. We call it the min-max objective function. In applications such as disaster relief efforts and military operations, the objective is often to finish the delivery or the task as soon as possible, not to plan routes with the minimum total distance. Even in commercial package delivery nowadays, companies are investing in new technologies to speed up delivery instead of focusing merely on the min-sum objective. In this dissertation, we compare the min-max and the standard (min-sum) objective functions in a worst-case analysis to show that the optimal solution with respect to one objective function can be very poor with respect to the other. The results motivate the design of algorithms specifically for the min-max objective. We study variants of min-max VRPs including one problem from the literature (the min-max Multi-Depot VRP) and two new problems (the min-max Split Delivery Multi-Depot VRP with Minimum Service Requirement and the min-max Close-Enough VRP). We develop heuristics to solve these three problems. We compare the results produced by our heuristics to the best-known solutions in the literature and find that our algorithms are effective. In the case where benchmark instances are not available, we generate instances whose near-optimal solutions can be estimated based on geometry. We formulate the Vehicle Routing Problem with Drones and carry out a theoretical analysis to show the maximum benefit from using drones in addition to trucks to reduce delivery time. The speed-up ratio depends on the number of drones loaded onto one truck and the speed of the drone relative to the speed of the truck.

Optimization of Energy Distribution in Solar Panel Array Configurations by Graph Theory and Minkowski’s Paths

Nowadays, the development of the photovoltaic (PV) technology is consolidated as a source of renewable energy. The research in the topic of maximum improvement on the energy efficiency of the PV plants is today a major challenge. The main requirement for this purpose is to know the performance of each of the PV modules that integrate the PV field in real time. In this respect, a PLC communications based Smart Monitoring and Communications Module, which is able to monitor at PV level their operating parameters, has been developed at the University of Malaga. With this device you can check if any of the panels is suffering any type of overriding performance, due to a malfunction or partial shadowing of its surface. Since these fluctuations in electricity production from a single panel affect the overall sum of all panels that conform a string, it is necessary to isolate the problem and modify the routes of energy through alternative paths in case of PV panels array configuration.

Host and Network Optimizations for Performance Enhancement and Energy Efficiency in Data Center Networks

Modern data centers host hundreds of thousands of servers to achieve economies of scale. Such a huge number of servers create challenges for the data center network (DCN) to provide proportionally large bandwidth. In addition, the deployment of virtual machines (VMs) in data centers raises the requirements for efficient resource allocation and find-grained resource sharing. Further, the large number of servers and switches in the data center consume significant amounts of energy. Even though servers become more energy efficient with various energy saving techniques, DCN still accounts for 20% to 50% of the energy consumed by the entire data center. The objective of this dissertation is to enhance DCN performance as well as its energy efficiency by conducting optimizations on both host and network sides. First, as the DCN demands huge bisection bandwidth to interconnect all the servers, we propose a parallel packet switch (PPS) architecture that directly processes variable length packets without segmentation-and-reassembly (SAR). The proposed PPS achieves large bandwidth by combining switching capacities of multiple fabrics, and it further improves the switch throughput by avoiding padding bits in SAR. Second, since certain resource demands of the VM are bursty and demonstrate stochastic nature, to satisfy both deterministic and stochastic demands in VM placement, we propose the Max-Min Multidimensional Stochastic Bin Packing (M3SBP) algorithm. M3SBP calculates an equivalent deterministic value for the stochastic demands, and maximizes the minimum resource utilization ratio of each server. Third, to provide necessary traffic isolation for VMs that share the same physical network adapter, we propose the Flow-level Bandwidth Provisioning (FBP) algorithm. By reducing the flow scheduling problem to multiple stages of packet queuing problems, FBP guarantees the provisioned bandwidth and delay performance for each flow. Finally, while DCNs are typically provisioned with full bisection bandwidth, DCN traffic demonstrates fluctuating patterns, we propose a joint host-network optimization scheme to enhance the energy efficiency of DCNs during off-peak traffic hours. The proposed scheme utilizes a unified representation method that converts the VM placement problem to a routing problem and employs depth-first and best-fit search to find efficient paths for flows.

A Multi-Criteria GIS-Based Route Selection Tool for Hazardous Material Transport: Consideration of Environmental Consequence, Traffic Congestions and Costs

Hazardous materials are substances that, if not regulated, can pose a threat to human populations and their environmental health, safety or property when transported in commerce. About 1.5 million tons of hazardous material shipments are transported by truck in the US annually, with a steady increase of approximately 5% per year. The objective of this study was to develop a routing tool for hazardous material transport in order to facilitate reduced environmental impacts and less transportation difficulties, yet would also find paths that were still compelling for the shipping carriers as a matter of trucking cost. The study started with identification of inhalation hazard impact zones and explosion protective areas around the location of hypothetical hazardous material releases, considering different parameters (i.e., chemicals characteristics, release quantities, atmospheric condition, etc.). Results showed that depending on the quantity of release, chemical, and atmospheric stability (a function of wind speed, meteorology, sky cover, time and location of accidents, etc.) the consequence of these incidents can differ. The study was extended by selection of other evaluation criteria for further investigation because health risk as an evaluation criterion would not be the only concern in selection of routes. Transportation difficulties (i.e., road blockage and congestion) were incorporated as important factor due to their indirect impact/cost on the users of transportation networks. Trucking costs were also considered as one of the primary criteria in selection of hazardous material paths; otherwise the suggested routes would have not been convincing for the shipping companies. The last but not least criterion was proximity of public places to the routes. The approach evolved from a simple framework to a complicated and efficient GIS-based tool able to investigate transportation networks of any given study area, and capable of generating best routing options for cargos. The suggested tool uses a multi-criteria-decision-making method, which considers the priorities of the decision makers in choosing the cargo routes. Comparison of the routing options based on each criterion and also the overall suitableness of the path in regards to all the criteria (using a multi-criteria-decision-making method) showed that using similar tools as the one proposed by this study can provide decision makers insights in the area of hazardous material transport. This tool shows the probable consequences of considering each path in a very easily understandable way; in the formats of maps and tables, which makes the tradeoffs of costs and risks considerably simpler, as in some cases slightly compromising on trucking cost may drastically decrease the probable health risk and/or traffic difficulties. This will not only be rewarding to the community by making cities safer places to live, but also can be beneficial to shipping companies by allowing them to advertise as environmental friendly conveyors.

Efficient algorithms for beacon routing in polygons

In a paper by Biro et al. [7], a novel twist on guarding in art galleries is introduced. A beacon is a fixed point with an attraction pull that can move points within the polygon. Points move greedily to monotonically decrease their Euclidean distance to the beacon by moving straight towards the beacon or sliding on the edges of the polygon. The beacon attracts a point if the point eventually reaches the beacon. Unlike most variations of the art gallery problem, the beacon attraction has the intriguing property of being asymmetric, leading to separate definitions of attraction region and inverse attraction region. The attraction region of a beacon is the set of points that it attracts. For a given point in the polygon, the inverse attraction region is the set of beacon locations that can attract the point. We first study the characteristics of beacon attraction. We consider the quality of a "successful" beacon attraction and provide an upper bound of $\sqrt{2}$ on the ratio between the length of the beacon trajectory and the length of the geodesic distance in a simple polygon. In addition, we provide an example of a polygon with holes in which this ratio is unbounded. Next we consider the problem of computing the shortest beacon watchtower in a polygonal terrain and present an $O(n \log n)$ time algorithm to solve this problem. In doing this, we introduce $O(n \log n)$ time algorithms to compute the beacon kernel and the inverse beacon kernel in a monotone polygon. We also prove that $\Omega(n \log n)$ time is a lower bound for computing the beacon kernel of a monotone polygon. Finally, we study the inverse attraction region of a point in a simple polygon. We present algorithms to efficiently compute the inverse attraction region of a point for simple, monotone, and terrain polygons with respective time complexities $O(n^2)$, $O(n \log n)$ and $O(n)$. We show that the inverse attraction region of a point in a simple polygon has linear complexity and the problem of computing the inverse attraction region has a lower bound of $\Omega(n \log n)$ in monotone polygons and consequently in simple polygons.

“Albedo dome”: a method for measuring spectral flux-reflectance in a laboratory for media with long optical paths

A method is presented for accurate measurement of spectral flux-reflectance (albedo) in a laboratory, for media with long optical path lengths, such as snow and ice. The approach uses an acrylic hemispheric dome, which, when placed over the surface being studied, serves two functions: (i) it creates an overcast “sky” to illuminate the target surface from all directions within a hemisphere, and (ii) serves as a platform for measuring incident and backscattered spectral radiances, which can be integrated to obtain fluxes. The fluxes are relative measurements and because their ratio is used to determine flux-reflectance, no absolute radiometric calibrations are required. The dome and surface must meet minimum size requirements based on the scattering properties of the surface. This technique is suited for media with long photon path lengths since the backscattered illumination is collected over a large enough area to include photons that reemerge from the domain far from their point of entry because of multiple scattering and small absorption. Comparison between field and laboratory albedo of a portable test surface demonstrates the viability of this method.

Query routing in cooperative semi-structured peer-to-peer information retrieval networks

Conventional web search engines are centralised in that a single entity crawls and indexes the documents selected for future retrieval, and the relevance models used to determine which documents are relevant to a given user query. As a result, these search engines suffer from several technical drawbacks such as handling scale, timeliness and reliability, in addition to ethical concerns such as commercial manipulation and information censorship. Alleviating the need to rely entirely on a single entity, Peer-to-Peer (P2P) Information Retrieval (IR) has been proposed as a solution, as it distributes the functional components of a web search engine – from crawling and indexing documents, to query processing – across the network of users (or, peers) who use the search engine. This strategy for constructing an IR system poses several efficiency and effectiveness challenges which have been identified in past work. Accordingly, this thesis makes several contributions towards advancing the state of the art in P2P-IR effectiveness by improving the query processing and relevance scoring aspects of a P2P web search. Federated search systems are a form of distributed information retrieval model that route the user’s information need, formulated as a query, to distributed resources and merge the retrieved result lists into a final list. P2P-IR networks are one form of federated search in routing queries and merging result among participating peers. The query is propagated through disseminated nodes to hit the peers that are most likely to contain relevant documents, then the retrieved result lists are merged at different points along the path from the relevant peers to the query initializer (or namely, customer). However, query routing in P2P-IR networks is considered as one of the major challenges and critical part in P2P-IR networks; as the relevant peers might be lost in low-quality peer selection while executing the query routing, and inevitably lead to less effective retrieval results. This motivates this thesis to study and propose query routing techniques to improve retrieval quality in such networks. Cluster-based semi-structured P2P-IR networks exploit the cluster hypothesis to organise the peers into similar semantic clusters where each such semantic cluster is managed by super-peers. In this thesis, I construct three semi-structured P2P-IR models and examine their retrieval effectiveness. I also leverage the cluster centroids at the super-peer level as content representations gathered from cooperative peers to propose a query routing approach called Inverted PeerCluster Index (IPI) that simulates the conventional inverted index of the centralised corpus to organise the statistics of peers’ terms. The results show a competitive retrieval quality in comparison to baseline approaches. Furthermore, I study the applicability of using the conventional Information Retrieval models as peer selection approaches where each peer can be considered as a big document of documents. The experimental evaluation shows comparative and significant results and explains that document retrieval methods are very effective for peer selection that brings back the analogy between documents and peers. Additionally, Learning to Rank (LtR) algorithms are exploited to build a learned classifier for peer ranking at the super-peer level. The experiments show significant results with state-of-the-art resource selection methods and competitive results to corresponding classification-based approaches. Finally, I propose reputation-based query routing approaches that exploit the idea of providing feedback on a specific item in the social community networks and manage it for future decision-making. The system monitors users’ behaviours when they click or download documents from the final ranked list as implicit feedback and mines the given information to build a reputation-based data structure. The data structure is used to score peers and then rank them for query routing. I conduct a set of experiments to cover various scenarios including noisy feedback information (i.e, providing positive feedback on non-relevant documents) to examine the robustness of reputation-based approaches. The empirical evaluation shows significant results in almost all measurement metrics with approximate improvement more than 56% compared to baseline approaches. Thus, based on the results, if one were to choose one technique, reputation-based approaches are clearly the natural choices which also can be deployed on any P2P network.

Vehicle routing and location routing problems with minimum latency: algorithms and models

Latency can be defined as the sum of the arrival times at the customers. Minimum latency problems are specially relevant in applications related to humanitarian logistics. This thesis presents algorithms for solving a family of vehicle routing problems with minimum latency. First the latency location routing problem (LLRP) is considered. It consists of determining the subset of depots to be opened, and the routes that a set of homogeneous capacitated vehicles must perform in order to visit a set of customers such that the sum of the demands of the customers assigned to each vehicle does not exceed the capacity of the vehicle. For solving this problem three metaheuristic algorithms combining simulated annealing and variable neighborhood descent, and an iterated local search (ILS) algorithm, are proposed. Furthermore, the multi-depot cumulative capacitated vehicle routing problem (MDCCVRP) and the multi-depot k-traveling repairman problem (MDk-TRP) are solved with the proposed ILS algorithm. The MDCCVRP is a special case of the LLRP in which all the depots can be opened, and the MDk-TRP is a special case of the MDCCVRP in which the capacity constraints are relaxed. Finally, a LLRP with stochastic travel times is studied. A two-stage stochastic programming model and a variable neighborhood search algorithm are proposed for solving the problem. Furthermore a sampling method is developed for tackling instances with an infinite number of scenarios. Extensive computational experiments show that the proposed methods are effective for solving the problems under study.

Message-oriented Middleware per Routing Acceleration basato su eBPF/XDP in Contesto Serverless

Negli ultimi anni la necessità di processare e mantenere dati di qualsiasi natura è aumentata considerevolmente, in aggiunta a questo, l’obsolescenza del modello centralizzato ha contribuito alla sempre più frequente adozione del modello distribuito. Inevitabile dunque l’aumento di traffico che attraversa i nodi appartenenti alle infrastrutture, un traffico sempre più in aumento e che con l’avvento dell’IoT, dei Big Data, del Cloud Computing, del Serverless Computing etc., ha raggiunto picchi elevatissimi. Basti pensare che se prima i dati erano contenuti in loco, oggi non è assurdo pensare che l’archiviazione dei propri dati sia completamente affidata a terzi. Così come cresce, quindi, il traffico che attraversa i nodi facenti parte di un’infrastruttura, cresce la necessità che questo traffico sia filtrato e gestito dai nodi stessi. L’obbiettivo di questa tesi è quello di estendere un Message-oriented Middleware, in grado di garantire diverse qualità di servizio per la consegna di messaggi, in modo da accelerarne la fase di routing verso i nodi destinazione. L’estensione consiste nell’aggiungere al Message-oriented Middleware, precedentemente implementato, la funzione di intercettare i pacchetti in arrivo (che nel caso del middleware in questione possono rappresentare la propagazione di eventi) e redirigerli verso un nuovo nodo in base ad alcuni parametri. Il Message-oriented Middleware oggetto di tesi sarà considerato il message broker di un modello pub/sub, pertanto la redirezione deve avvenire con tempi molto bassi di latenza e, a tal proposito, deve avvenire senza l’uscita dal kernel space del sistema operativo. Per questo motivo si è deciso di utilizzare eBPF, in particolare il modulo XDP, che permette di scrivere programmi che eseguono all’interno del kernel.

Sviluppo e validazione di un algoritmo di Vehicle Routing per un caso di logistica distributiva in collaborazione con Toyota Material Handling Italia

L’elaborato descrive le fasi di progettazione, programmazione e validazione di un programma sviluppato in ambiente Java per il Vehicle Routing Problem. L’algoritmo implementato è di tipo euristico costruttivo primal e presenta funzionalità specifiche per la gestione di un elevato numero di vincoli e l’applicazione a casistiche reali. La validazione è stata effettuata su una base dati reale e in confronto a dataset di cui è nota la soluzione ottima. Il programma è stato progettato per risultare flessibile alle richieste dell’utente e utilizzabile per valutazioni economiche in ambito consulenziale.

Analisi e studio computazionale di solver per problemi di routing di interesse industriale

Il Routing rappresenta uno dei problemi più studiati nell’ambito della Ricerca Operativa in quanto offre molteplici possibilità di ottimizzazione da cui possono derivare altrettanti vantaggi per le aziende che decidono di gestirlo in maniera strutturata. Uno dei principali ambiti di applicazione del routing è la pianificazione operativa del trasporto merci a clienti sparsi in un determinato territorio. Ci sono aziende che devono organizzare la loro Logistica distributiva ogni giorno. Ormai è diventato evidente che la realizzazione di questo processo mediante modalità “standard”, senza l’utilizzo di appositi strumenti di ottimizzazione, non solo porta alla perdita di occasioni importanti in termini di vantaggi raggiungibili, ma è anche molto più dispendiosa a livello di tempo richiesto. Molte aziende si stanno quindi affidando a soluzioni SW che si vadano ad integrare con i loro processi decisionali. Questi sistemi hanno alla base delle componenti algoritmiche in grado di trovare la migliore soluzione possibile per la tipologia specifica di Routing da affrontare. Per questi motivi, lo sviluppo di algoritmi in grado di risolvere questo problema rappresenta una parte consistente della letteratura scientifica in ambito di ottimizzazione. In questo elaborato si andranno a definire le principali caratteristiche di un problema di Routing in forma base e nelle sue varianti principali. Si descriveranno le caratteristiche dei problemi di Routing incontrati da Optit S.r.l, un’azienda che opera nel settore dello sviluppo di soluzioni SW di ottimizzazione. Nel fare ciò, si cercherà di trovare sovrapposizione con quanto descritto in letteratura. Infine, si descriveranno alcuni solver Open-Source per risolvere problemi di Routing e si mostreranno i risultati da essi ottenuti su alcuni casi di interesse industriale.