In this study, the design of a three-level distribution system is considered in which a single supplier ships a number of items to the retailers via a set of distribution centers (DC) and stochastic demand is observed at the retailers. The problem is to specify the number and location of the DCs, and the assignment of the retailers to the DCs in such a way that total facility, transportation, safety stock, and joint ordering and average inventory costs are minimized, and customer service requirements are satisfied. Single source constraints are imposed on the assignment of the retailers to the DCs. The integrated location/inventory model incorporates the inventory management decisions into the strategic location/allocation decisions by considering the benefits of risk pooling and the savings that result in the joint replenishment of a group of items. We develop two heuristic methods to solve the non-linear integer-programming model in an integrated way: (1) Improvement type heuristic, (2) Constructive type heuristic. The heuristic algorithms are tested on a number of problem instances with 81 demand points (retailers) and 4 different types of items. Both of the heuristics are able to generate solutions in very reasonable times. The results are compared to the results of the p-median problem and found that the total cost and the number of DCs can be lowered using our integrated model instead of the p-median problem. Finally, sensitivity analysis is performed with respect to the changes in inventory, transportation, and ordering cost parameters, and variability of the demand.

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Made available in DSpace on 2016-06-02T19:51:45Z (GMT). No. of bitstreams: 1 3178.pdf: 5667245 bytes, checksum: c48bc6ad36e2a190f7ec6207752bd88b (MD5) Previous issue date: 2010-06-02 / Universidade Federal de Sao Carlos / Soybean is one of the most important agricultural products grown in Brazil. Comparing to the total volume of grain produced, soybean corresponds to approximately 44% and the midwest region is the largest soybean producer in Brazil. Because of that, the soybean that goes for export, on average, have to go over large distances to reach the maritime ports from where it is exported. Transport costs represent approximately 25% of the total cost what influences directly on the product price in international market. Loading transportation over long distances, such as the Brazilian soybean flows, the intermodal transportation is an alternative to make the soybean flows for export more economical. The efficient loading transportation using more than one modal depends not only on the availability of the transport itself but also on support infrastructure, such as intermodal terminals. In order to support decisions regarding the design and operation of the network flow of soybean for export, this work proposes using a mathematical programming model based on the Theory of Facilities Location to locate intermodal terminals in the network, taking into account not only the physical network, but also flows of soybeans that are moved by its vertices and arcs. We made several computational preliminary tests to verify the adequacy of the model to the reality we want to represent. Given the adequacy of the model, new experiments were done on a network that represents more realistically the present situation of the soybean flows in Brazil. / A soja é um dos principais produtos agrícolas produzidos pelo Brasil. Em relação ao volume total de grãos produzidos, a soja corresponde à aproximadamente 44%, sendo a região Centro-Oeste a maior produtora do grão no Brasil. Por isso, a soja em grão destinada à exportação percorre, em média, grandes distâncias para chegar aos portos marítimos por onde é exportada. Os custos de transporte correspondem à cerca de 25% do custo total, influenciando de forma direta no preço do produto no mercado internacional. Para o transporte de cargas por longas distâncias, como é o caso do escoamento da soja brasileira, a intermodalidade de transporte surge como uma alternativa para tornar a movimentação da soja destinada à exportação mais econômica. O funcionamento eficiente do transporte de uma carga por mais de um modal depende não só da disponibilidade do modal em si, mas também de uma infraestrutura de apoio, como terminais intermodais. Como forma de apoiar decisões relativas ao projeto e operacionalização da rede de escoamento da soja em grão destinada à exportação, esta pesquisa propõe a utilização de um modelo de programação matemática baseado da Teoria de Localização de Instalações para localizar terminais intermodais nesta rede, levando em consideração não só a rede física, como também os fluxos de soja que são movimentados por seus vértices e arcos. Foram feitos diversos testes computacionais preliminares para verificar a adequação do modelo à realidade que se deseja representar. Diante da adequação do modelo, foram feitos novos experimentos em uma rede que representa de forma mais realista a situação atual dos fluxos de soja em grão pelo Brasil.

O presente estudo trata da configuração de uma rede de distribuição capacitada com restrição de cobertura. O objetivo é determinar quais cidades, dentre um conjunto de candidatas, devem atuar como centrais de desconsolidação de carga, de forma a minimizar o custo total de transporte (transferência e distribuição) para uma determinada demanda, atendendo às restrições operacionais e de distância de cobertura. A partir da pesquisa na literatura sobre o assunto, foi preparado um modelo de programação linear inteira para encontrar a solução ótima para o problema. Esse modelo é baseado nos clássicos problemas de localização, com modificação na função objetivo para retratar melhor a estrutura de custos de transporte, além da inclusão de restrições de cobertura e restrições de atendimento mínimas e máximas em cada central. O modelo foi implementado utilizando o suplemento Solver da planilha eletrônica Excel. Um outro enfoque de solução baseado na metaheurística Busca Tabu (Tabu Search) foi elaborado, com dois objetivos: permitir a análise de problemas quando não se tem disponível uma ferramenta para solução de modelos de programação linear; e analisar o comportamento da metaheurística quando utilizada na solução desse tipo de problema. O procedimento foi implementado a partir da construção de macros em linguagem Visual Basic for Application (VBA), também em Excel. O modelo de programação linear e a metaheurística Busca Tabu foram aplicados a alguns cenários de um problema real. Resultados, comparações e conclusões dessas aplicações são apresentados neste trabalho. / The present study deals with configuring a capacitated distribution network with coverage constraint. The objective consists of determining which cities, among a set of candidates, should act as load deconsolidation centers, aiming to minimize transportation total costs to attend a given demand, and obeying all operational constraints and coverage distances. Based on a literature review, an integer linear programming model was formulated to find the problem optimal solution. The model is based on classical location problems, but includes changes in the objective function to incorporate the transportation costs structure, besides coverage constraints and minimum and maximum central capacity constraints. The model was implemented using Excel’s Solver add-in. Another solution approach based on the Tabu Search metaheuristic was proposed, with two objectives: to permit problem analysis when linear programming tools are not available; and to learn on metaheuristic behavior when used to solve this type of problem. The Tabu Search procedure was implemented using Excel macro language in Visual Basic for Applications (VBA). Both integer linear programming and metaheuristic models were applied to some scenarios of a real-world problem. Applications results, comparisons and conclusions are presented in this work.

In spatial analysis, many operations are performed considering the neighbouring locations of a feature. The standard definition of a neighbourhood is an area confined by geometrical length and direction with respect to its focus. When allocating a location for a service, the population distribution is often considered. Standard GIS software includes tools for computations with uniform neighbourhoods, usually equal sized circles. These tools can be used for distribution analysis. Many geographic studies used as basis for city planning decisions use distance as an evaluator. It is a frequent occurrence that the actual distance is approximated using factored straight-line distance. For great distances and large datasets, this is a sufficient means of evaluation, whilst for smaller distances for specific locations, it poses major drawbacks. For distribution analysis in a network space, the neighbourhood would need to be derived from the local set of network features, creating a unique neighbourhood for each location. The neighbourhood can then be used to overlay other datasets to perform analysis of features within the network space. This report describes the application of network distance based neighbourhoods to design a tool, Network Location Analysis, for calculating focal statistics for use as a city planning decision support. The tool has been implemented as a workflow of ArcGIS tools scripted as a Python toolbox. The input required by the tool is a population point layer and a vector network dataset. The output is a grid of points with population statistics as attributes and corresponding neighbourhoods generalized as polygons. The tool has been tested by comparing it to standard focal operations implemented in ArcGIS and by applying it to the dataset used when conducting a study on the location of a new metro station using conventional ArcGIS tools. The results have been analysed and visualized and compared to data used in the study. The result concludes that Network Location Analysis surpasses conventional ArcGIS tools when conducting analysis on features in a network. It derives an accurate set of sum and proximity statistics for all locations within the processing extent, enabling analysis on the population distribution throughout the area and for specific points. The output is intuitive, manageable and can be visualized as raster or by displaying the neighbourhoods as polygons and can be used to evaluate population distribution and network connectivity. The drawbacks of the tool are its lack of robustness, its rigidity to input and the inefficient implementation causing execution time to be unpractical.

LKAB hanterar en av världens största malmkroppar vid en underjordsgruva i Kiruna. I samband med deras gruvbrytning uppstår stora mängder avfall som måste hanteras korrekt. De avfallsanläggningar som finns på området har idag platsbrist, därför finns incitament att bygga nya anläggningar. Inför utformningen av dessa nya anläggningar behöver avfallsflöden inventeras och analyseras. I detta arbete har det skett med diskret händelsesimulering baserad på historisk data. På grund av osäkra parametrar har flera scenarion tagits fram. Utformningen av anläggningarna beror på vilken kapacitet de förväntas ha, vilket är beroende av hur ofta anläggningarna ska tömmas och hur mycket avfall som förväntas uppstå på gruvområdet. För att sedan hitta bästa möjliga placering på de nya anläggningarna har ett modifierat anläggningslokaliseringsproblem tillämpats. Den optimala placeringen är i den norra delen av gruvområdet och minskar den totala körsträckan. Placeringen påverkas inte av större flöden. / In Kiruna the company LKAB has an underground mine with one of the largest iron ore quantities in the world. When producing the iron ore, a lot of waste arise that has to be taken care of in a correct way. Due to lack of space in todays waste facilities, there exists incentives to build new ones. To be able to design these new facilities, the flows of waste has to be investigated and analyzed. This has been done by discrete-event simulation based on historical data. Since some of the collected parameters are uncertain, different scenarios have been tested. The design of the facilities are dependent on what capacity they are expected to store, which is dependent on how often the facilities will be emptied and how large quantities will arise in the mining area. To find an optimal placement for the new facilities, a modified facility location problem has been implemented. The optimal placement is in the north part of LKAB’s mining area and will lower the total driving distance. The optimal placement will not be affected by larger flows.

Network virtualization has become a primary enabler to solve the internet ossi- fication problem. It allows to run multiple architectures or protocols on a shared physical infrastructure. One of the important aspects of network virtualization is to have a virtual network (VN) mapping technique which uses the substrate resources efficiently. Currently, there exists very few VN mapping techniques and there is no common evaluation strategy which can test these algorithms effectively. In this thesis, we advocate the need for such a tool and develop it by considering a wide spectrum of parameters and simulation scenarios. We also provide various performance metrics and do a comparison study of the existing algorithms. Based on the comparative study, we point out the positives and negatives of the existing mapping algorithms and propose a new LP formulation based on Hub location approach that efficiently allocates substrate resources to the virtual network requests. Our results show that our algorithm does better in terms of number of successful network mappings and average time to map while balancing load on the network.

Indiana University-Purdue University Indianapolis (IUPUI) / The aging infrastructure of a wastewater collection system can leak, capture ground water, and capture precipitation runoff. These are some of the most common problems in many of today’s US collection systems and are often collectively referred to as Rain Derived Inflow and Infiltration (RDII or I/I). The goal of this study is to investigate such optimized methods and their potential to improve flow monitor placement, especially for RDII studies, and to improve upon Stevens (2005) methodology. This project adopts a methodology from the “facility location problem”, a branch of operations research and graph theory. Solutions to a facility location problem will be adapted and utilized within a transportation GIS application to determine optimal placement.

With unmanned aerial vehicle(s) (UAV), swift responses to urgent needs (such as search and rescue missions or medical deliveries) can be realized. Simultaneously, legislators are establishing so-called geographical zones, which restrict UAV operations to mitigate air and ground risks to third parties. These geographical zones serve particular safety interests but they may also hinder the efficient usage of UAVs in time-critical missions with range-limiting battery capacities. In this study, we address a facility location problem for up to two UAV hangars and combine it with a routing problem of a standard UAV mission to consider geographical zones as restricted areas, battery constraints, and the impact of wind to increase the robustness of the solution. To this end, water rescue missions are used exemplary, for which positive and negative location factors for UAV hangars and areas of increased drowning risk as demand points are derived from open-source georeferenced data. Optimum UAV mission trajectories are computed with an A* algorithm, considering five different restriction scenarios. As this pathfinding is very time-consuming, binary occupancy grids and image-processing algorithms accelerate the computation by identifying either entirely inaccessible or restriction-free connections beforehand. For the optimum UAV hangar locations, we maximize accessibility while minimizing the service times to the hotspots, resulting in a decrease from the average service time of 570.4 s for all facility candidates to 351.1 s for one and 287.2 s for two optimum UAV hangar locations.

Thesis (MComm)--Stellenbosch University, 2013. / ENGLISH ABSTRACT: FoodBank South Africa is an non-profit organisation formed to establish a national network of community foodbanks in urban and rural areas of South Africa, with all participants working towards the common goal of eliminating hunger and food insecurity. FoodBank Cape Town was the first of these community foodbanks launched in South Africa on 2 March 2009. The operations of FoodBank Cape Town include sourcing food and redistributing it to agencies (social services organisations running feeding programmes). Currently the majority of the food is sourced from the retail sector and then redistributed to approximately two hundred agencies. The logistics involved in both sourcing and distributing food are vital to the efficient functioning of FoodBank Cape Town. Since the costs associated with these logistics operations are very high, streamlining these operations has been identified as a priority area for efficiency improvement. The focus in this thesis is on the distribution logistics involved, specifically focussing on a facility location problem according to which FoodBank Cape Town can establish local distribution depots to which it delivers food and from which the agencies collect food assigned to them. A mixed-integer programming model is formulated for the above facility location problem and small test instances of the problem are solved using different exact and approximate solution methods in order to identify a suitable solution methodology for the full (large-scale) FoodBank Cape Town facility location problem. The full facility location problem is solved approximately by means of a meta-heuristic solution method in the more highly constrained instances, while an exact method is selected for solving the lesser constrained instances. The problem is first solved based on the distances between the warehouse and the depots as well as the distances between the agencies and the depots, for the twenty four instances where 17 to 40 depots are located. The model is then developed further to incorporate the cost of distribution. This cost-based facility location model is solved with a view to minimise the cost of food distribution from the warehouse to the depots and the cost of food distribution incurred by each agency to collect food from its assigned depot. A basic vehicle routing technique is applied to the cost-based facility location solution and the associated costs of the distribution are updated. This cost-based solution updating process is performed iteratively until the solution converges. Since the cost of food distribution depends on the vehicle fleet composition used, a vehicle fleet composition comparison of possible FoodBank Cape Town vehicles is performed to determine the most desirable vehicle fleet composition to be used for the distribution of food to depots. The results of the FoodBank Cape Town facility location problem and vehicle fleet composition comparison are presented and recommendations are made to FoodBank Cape Town regarding the preferred number of depots, the location of these depots and the preferred vehicle fleet composition. / AFRIKAANSE OPSOMMING: FoodBank South Africa is ’n nie-winsgewende organisasie wat ten doel het om ’n nasionale netwerk van gemeenskapsvoedselbanke in stedelike en landelike gebiede van Suid-Afrika op die been te bring, waarin al die deelnemers die gemeenskaplike doel nastreef om honger en voedselonsekerheid te elimineer. Foodbank Cape Town was die eerste van hierdie gemeenskapsvoedselbanke in Suid-Afrika en is op 2 Maart 2009 gestig. Die take van Foodbank Cape Town sluit in die versameling van voedsel en die verspreiding daarvan aan agentskappe (gemeenskapsorganisasies wat voedingsprogramme bestuur). Die oorgrote meerderheid voedsel is tans uit die kleinhandelsektor afkomstig en word aan ongeveer tweehonderd agentskappe versprei. Die logistiek wat met hierdie versamelings- en verspreidingsprosesse gepaard gaan, is sentraal tot die doeltreffende funksionering van FoodBank Cape Town. Aangesien die kostes verbonde aan hierdie logistieke prosesse baie hoog is, is hierdie aktiwiteite as ’n prioriteitsarea vir verbetering geidentifiseer. Die fokus in hierdie tesis val op die logistiek verbonde aan die verspreiding van voedsel deur FoodBank Cape Town, en meer spesifiek op die probleem van die plasing van ’n aantal lokale verspreidingsdepots waar FoodBank Cape Town voedsel kan aflewer en waar die agentskappe dan voedsel wat aan hulle toegeken is, kan gaan afhaal. ’n Gemengde heeltallige-programmeringsmodel word vir die bogenoemde plasingsprobleem geformuleer en klein gevalle van die model word deur middel van beide eksakte en benadere oplossingstegnieke opgelos om sodoende ’n geskikte oplossingsmetode vir die volle (grootskaalse) Food- Bank Cape Town plasingsmodel te identifiseer. Die volle plasingsmodel word aan die hand van ’n metaheuristiese oplossingstegniek benaderd opgelos vir hoogsbeperkte gevalle van die model, terwyl minder beperkte gevalle van die model eksak opgelos word. Die plasingsmodel word eers met die oog op die minimering van afstande tussen die pakhuis en verspreidingsdepots sowel as tussen die verspreidingsdepots en agentskappe vir die vier-en-twintig gevalle van die plasing van 17 tot 40 verspreidingsdepots opgelos. Die model word dan verder ontwikkel om ook die koste van die verspreiding van voedsel in ag te neem. Die koste-gebaseerde plasingsmodel word opgelos met die doel om die voedselbankkoste van voedselverspreiding vanaf die pakhuis na die lokale verspreidingsdepots sowel as die agentskapkoste van die afhaal van voedsel vanaf verspreidingsdepots te minimeer. ’n Basiese voertuigroeteringstegniek word op die koste-gebaseerde plasingsmodel toegepas en die verspreidingskoste word dienooreenkomstig aangepas. Hierdie aanpassingsproses van die koste-gebaseerde oplossing word herhaal totdat die oplossing konvergeer. Aangesien die koste van voedselverspreiding afhang van die voertuigvlootsamestelling, word ’n vergelyking tussen moontlike vlootsamestellings vir FoodBank Cape Town getref om die mees geskikte samestelling van voertuie vir die verspreiding van voedsel te vind. Die resultate van die FoodBank Cape Town verspreidingsdepot-plasingsprobleem en vlootsamestellingsvergelyking word aangebied en ’n aanbeveling word aan FoodBank Cape Town gemaak in terme van ’n geskikte aantal verspreidingsdepots, waar hierdie depots geleë behoort te wees, en ’n geskikte voertuigvlootsamestelling vir die verspreiding van voedsel.