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.

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.

The 'Arc of prosperity' revisited: Homelessness policy change in north western Europe

This paper compares continuity and change in homelessness policy in Ireland, Scotland and Norway with a particular focus on the period of post-crisis austerity measures (2008-2016). The analytical approach draws on institutional theory and the notion of path dependency, which has rarely been applied to comparative homelessness research. The paper compares welfare and housing systems in the three countries prior to presenting a detailed analysis of the conceptualisation and measurement of homelessness; the institutions which address homelessness; and the evidence of change in the post-2008 period. The analysis demonstrates that challenges remain in comparing the nature of homelessness and policy responses across nation states, even where they have a number of similar characteristics, and despite some EU influence towards homelessness policy convergence. Similarly, national-level homelessness policy change could not be interpreted as entirely a result of the external shock of the 2008 general financial crisis, as existing national policy goals and programmes were also influential. Overall, embedded national frameworks and institutions were resilient, but sufficiently flexible to deliver longer term policy shifts in response to the changing nature of the homelessness problem and national policy goals. Institutionalism and path dependency were found to be useful in developing the comparative analysis of homelessness policy change and could be fruitfully applied in future longitudinal, empirical research across a wider range of countries.

A comparative study of the structural, mechanical and tribological characteristics of TiSiC-Cr coatings prepared in CH4 and C2H2 reactive atmosphere by cathodic vacuum arc

TiSiC-Cr coatings, with Cr and Si as additional elements, were deposited on Si, C 45 and 316 L steel substrates via cathodic arc evaporation. Two series of coatings with thicknesses in the range of 3.6–3.9 μm were produced, using either CH4 or C2H2 as carbon containing gas. For each series, different coatings were prepared by varying the carbon rich gas flow rate between 90 and 130 sccm, while maintaining constant cathode currents (110 and 100 A at TiSi and Cr cathodes, respectively), substrate bias (–200 V) and substrate temperature (∼320 °C). The coatings were analyzed for their mechanical characteristics (hardness, adhesion) and tribological performance (friction, wear), along with their elemental and phase composition, chemical bonds, crystalline structure and cross-sectional morphology. The coatings were found to be formed with nano-scale composite structures consisting of carbide crystallites (grain size of 3.1–8.2 nm) and amorphous hydrogenated carbon. The experimental results showed significant differences between the two coating series, where the films formed from C2H2 exhibited markedly superior characteristics in terms of microstructure, morphology, hardness, friction behaviour and wear resistance. For the coatings prepared using CH4, the measured values of crystallite size, hardness, friction coefficient and wear rate were in the ranges of 7.2–8.2 nm, 26–30 GPa, 0.3–0.4 and 2.1–4.8 × 10−6 mm3 N−1 m−1, respectively, while for the coatings grown in C2H2, the values of these characteristics were found to be in the ranges of 3.1–3.7 nm, 41–45 GPa, 0.1–0.2 and 1.4–3.0 × 10−6 mm3 N−1 m−1, respectively. Among the investigated coatings, the one produced using C2H2 at the highest flow rate (130 sccm) exhibited the highest hardness (45.1 GPa), the lowest friction coefficient (0.10) and the best wear resistance (wear rate of 1.4 × 10−6 mm3 N−1 m−1).

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.