This thesis if focused on brand building on the internet and possibilities brought to this filed by usage of systems methodologies. SWOT analysis is widely used in marketing, but it is focused solely on evaluating the current state of things and there is no formal framework to connect branding with marketing. Critical Systems Heuristics (CSH) methodology is used to supplement traditional marketing approaches. CSH consists of 12 boundary questions which can be used to define ideal state of analyzed systems. CSH methodology is then used to create a draft of Monoe brand, which will stand for a provider of photographical and graphical services. Based on gathered information from boundary questions, a website for the brand was created and promotion on social networks was also started. This practical use of CSH shoved that the boundary questions are too vague to be properly used in branding, but mostly address the right fields. Because of that, the boundary questions were modified. The asset of this thesis is modifying CSH methodology so it can be used as a framework to build brands on the internet.

Please read the abstract in the section 00front of this document / Thesis (PhD (Technology Management))--University of Pretoria, 2008. / Graduate School of Technology Management (GSTM) / unrestricted

O problema de dimensionamento de lotes determina um plano de produção que apoia às tomadas de decisões, a médio prazo, em meios industriais. Este plano de produção indica as quantidades de cada item que devem ser produzidas em cada período do horizonte de planejamento, de acordo com um objetivo dado e satisfazendo a demanda dos clientes. Diversos métodos de solução foram propostas na literatura, considerando a dificuldade de solução de algumas classes de problemas e a necessidade de métodos que gerem soluções de alta qualidade em um tempo computacional adequado. Neste trabalho, abordamos heurísticas baseadas na formulação matemática (LP-and-fix, relax-and-fix e fix-and-optimize), uma metaheurística (algoritmo de abelhas) e dois métodos híbridos, utilizados na solução de dois problemas distintos de dimensionamento de lotes multiestá- gio com limitação de capacidade. Consideramos também, a utilização de três formulações da literatura, para verificar a influência de cada uma sobre as abordagens de solução verificadas. Os resultados computacionais demonstraram que os métodos baseados na formulação matemática do problema se mostraram eficientes, mas limitados normalmente a ótimos locais, enquanto os métodos híbridos puderam superar estes ótimos locais, utilizando conceitos da metaheurística algoritmo de abelhas para isto. Além disso, pudemos verificar a influência de uma formulação \"forte\" sobre as soluções geradas pelas abordagens de solução, demonstrando que métodos baseados em relaxação linear conseguem obter maiores vantagens deste tipo de formulação, mas outras abordagens podem ou não obter estas vantagens, dependendo do problema abordado / The lot-sizing problem determines a production plan, which supports the decision making, in the medium term, at the industrial environment. This production plan indicates the amounts of each item to be produced in each period of the planning horizon, according to a given objective and satisfying customer\'s demand. Diverse solution methods have been proposed in the literature, considering the difficulty of solving some problem classes and the need of methods to generate solutions quickly. In this work, we develop matheuristics (LP-and-fix, relax-and-fix and fix-and-optimize), one metaheuristic (bees algorithm) and two hybrid methods, used to solve two different multilevel capacitated lot-sizing problems. We also consider the use of three different formulations of the literature to verify the influence of each one on the solutions approaches. The computational results show that the matheuristics proved to be efficient, but usually limited to local optima, while the hybrid methods could escape from these local optima, using concepts of bees algorithm to do this. Additionally, we test the effect of a tight formulation on the solutions approaches, demonstrating that LP-based heuristics can obtain further advantages from this type of formulation, but other approaches can take these advantages, depending on the problem addressed

Cadeias de suprimentos podem ter operações seguindo diferentes estratégias de distribuição e a utilização de cada uma dessas estratégias pode resultar em diferentes operações e custos. A estratégia de cross-docking auxilia na redução dos custos de distribuição de produtos, consolidando cargas, e a redução de tempo e custos de armazenamento, uma vez que o tempo máximo de estoque permitido pela estratégia é de cerca de 24 horas. O objetivo deste trabalho é apresentar um modelo para o problema de cross-docking, em que cargas são entregues e reorganizadas de forma a atender a outras cargas que são coletadas e garantir que as janelas de tempo para início das operações sejam atendidas. Devido à falta de instâncias para o problema disponíveis na literatura, buscou-se gerar um benchmark e disponibilizá-las à comunidade científica. Uma vez que o problema é de difícil solução exata, um método heurístico para a resolução do problema foi desenvolvido. Os resultados mostraram que o modelo proposto resulta em boas soluções quando comparado ao modelo da literatura. O estudo de calibração do software IBM CPLEX mostrou que a calibração dos parâmetros pode resultar em melhores soluções e, por fim, a matheurística se mostrou competitiva com o CPLEX, principalmente para cenários em que a proporção de entregas e coletas diverge. / Supply chains may have operations which follow different distribution strategies and each one of these strategies may result in different operations and costs. The Cross-docking strategy helps to reduce the products distribution costs by consolidating loads and reducing storage costs as the maximum inventory time is approximately 24 hours. The aim of this research is to present a model for the cross-docking problem where loads are delivered and reorganized so as to cater for other loads that are collected and ensure that time windows are respected. Due to the lack of instances available in the literature, a benchmark was generated and was made available to the scientific community. As the problem is difficult to obtain the exact solution, a heuristic method was developed. The results showed that the proposed model has good solutions when compared to the literature model. A study of the IBM CPLEX software showed that tuning can result in better solutions and the matheuristcs was competitive with the software, mainly in scenarios where deliveries and pickups are very different.

O problema de empacotamento de itens irregulares com balanceamento da carga é encontrado no carregamento de aviões, caminhões e navios. O objetivo é empacotar itens irregulares utilizando o menor número de recipientes possível de forma que os recipientes estejam balanceados, que os itens não se sobreponham e estejam inteiramente contidos no recipiente. Neste trabalho, propomos três heurísticas bases com três variações cada para o problema com recipientes retangulares e irregulares. As heurísticas utilizam abordagens diferentes para representar os itens e para fazer o balanceamento. Uma das heurísticas utiliza malha para representação dos itens e faz o balanceamento dividindo o recipiente em quadrantes e revezando a alocação dos itens entre eles de forma que o balanceamento é feito de forma indireta. Tal heurística resolve o problema tanto para recipientes retangulares quanto irregulares. A segunda heurística utiliza a representação dos itens por polígonos e impossibilita a sobreposição de itens utilizando a técnica do nofit polygon. A heurística constrói a solução item por item, sem posições fixas e a cada item alocado, os itens são deslocados em direção ao centro de gravidade desejado do recipiente. Esta heurística resolve apenas problemas com recipientes retangulares. A última heurística é uma adaptação da heurística anterior para a resolução do problema com recipientes irregulares, de forma que o problema é resolvido em duas fases. Cada heurística base possui três variações cada, totalizando nove heurísticas. As heurísticas foram comparadas com outro trabalho da literatura e conseguiram melhorar os resultados para nove das dezenove instâncias testadas. / The irregular bin packing problem with load balancing is found in the loading of airplanes, trucks and ships. The aim is to use as few bins as possible to pack all the items so that all bins are balanced, items do not overlap and are fully contained in the bin. In this work, we propose three base heuristics with three variations each for the problem with rectangular and irregular bin. The three heuristics use different approaches to represent the items and to balance the bin. One of the heuristics uses a grid to represent the items and does the balancing by dividing the container into quadrants and alternating the allocation of items between them so that the balancing is done indirectly. Such heuristic solves the problem for both rectangular and irregular bins. The second heuristic uses the representation of items by polygons and uses the nofit polygon technique. The heuristic constructs the solution item by item, with no fixed positions and with each item allocated, the items are shifted towards the desired center of gravity of the bin. This heuristic only solves problems with rectangular bins. The last heuristic is an adaptation of the previous one to solve the problem with irregular bins, so that the problem is solved in two phases. Each base heuristic has three variations, totaling nine heuristics. The heuristics were compared with other work in the literature and managed to improve the results for nine of the nineteen instances tested.

The characterization of the mechanical behavior of soft living tissues is a big challenge in Biomechanics. The difficulty arises from both the access to the tissues and the manipulation in order to know their physical properties. Currently, the biomechanical characterization of the organs is mainly performed by testing ex-vivo samples or by means of indentation tests. In the first case, the obtained behavior does not represent the real behavior of the organ. In the second case, it is only a representation of the mechanical response of the indented areas. The purpose of the research reported in this thesis is the development of a methodology to in-vivo characterize the biomechanical behavior of two different organs: the breast and the cornea. The proposed methodology avoids invasive measurements to obtain the mechanical response of the organs and is able to completely characterize of the biomechanical behavior of them. The research reported in this thesis describes a methodology to in-vivo characterize the biomechanical behavior of the breast and the cornea. The estimation of the elastic constants of the constitutive equations that define the mechanical behavior of these organs is performed using an iterative search algorithm which optimizes these parameters. The search is based on the iterative variation of the elastic constants of the model in order to increase the similarity between a simulated deformation of the organ and the real one. The similarity is measured by means of a volumetric similarity function which combines overlap-based coefficients and distance-based coefficients. Due to the number of parameters to be characterized as well as the non-convergences that the solution may present in some regions, genetic heuristics were chosen to drive the search algorithm. In the case of the breast, the elastic constants of an anisotropic hyperelastic neo-Hookean model proposed to simulate the compression of the breast during an MRI-guided biopsy were estimated. Results from this analysis showed that the proposed algorithm accurately found the elastic constants of the proposed model, providing an average relative error below 10%. The methodology was validated using breast software phantoms. Nevertheless, this methodology can be easily transferred into its use with real breasts. In the case of the cornea, the elastic constants of a hyperelastic second-order Ogden model were estimated for 24 corneas corresponding to 12 patients. The finite element method was applied in order to simulate the deformation of the human corneas due to non-contact tonometry. The iterative search was applied in order to estimate the elastic constants of the model which approximates the most the simulated deformation to the real one. Results showed that these constants can be estimated with an error of about 5%. After the results obtained for both organs, it can be concluded that the iterative search methodology presented in this thesis allows the \textit{in-vivo} estimation the patient-specific elastic constants of the constitutive biomechanical models that govern the biomechanical behavior of these two organs. / Lago Ángel, MÁ. (2014). A new approach for the in-vivo characterization of the biomechanical behavior of the breast and the cornea [Tesis doctoral no publicada]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/44116 / TESIS

Despite the continuous evolution in computers and information technology, real-world combinatorial optimization problems are NP-problems, in particular in the domain of planning and scheduling. Thus, although exact techniques from the Operations Research (OR) field, such as Linear Programming, could be applied to solve optimization problems, they are difficult to apply in real-world scenarios since they usually require too much computational time, i.e: an optimized solution is required at an affordable computational time. Furthermore, decision makers often face different and typically opposing goals, then resulting multi-objective optimization problems. Therefore, approximate techniques from the Artificial Intelligence (AI) field are commonly used to solve the real world problems. The AI techniques provide richer and more flexible representations of real-world (Gomes 2000), and they are widely used to solve these type of problems. AI heuristic techniques do not guarantee the optimal solution, but they provide near-optimal solutions in a reasonable time. These techniques are divided into two broad classes of algorithms: constructive and local search methods (Aarts and Lenstra 2003). They can guide their search processes by means of heuristics or metaheuristics depending on how they escape from local optima (Blum and Roli 2003). Regarding multi-objective optimization problems, the use of AI techniques becomes paramount due to their complexity (Coello Coello 2006). Nowadays, the point of view for planning and scheduling tasks has changed. Due to the fact that real world is uncertain, imprecise and non-deterministic, there might be unknown information, breakdowns, incidences or changes, which become the initial plans or schedules invalid. Thus, there is a new trend to cope these aspects in the optimization techniques, and to seek robust solutions (schedules) (Lambrechts, Demeulemeester, and Herroelen 2008). In this way, these optimization problems become harder since a new objective function (robustness measure) must be taken into account during the solution search. Therefore, the robustness concept is being studied and a general robustness measure has been developed for any scheduling problem (such as Job Shop Problem, Open Shop Problem, Railway Scheduling or Vehicle Routing Problem). To this end, in this thesis, some techniques have been developed to improve the search of optimized and robust solutions in planning and scheduling problems. These techniques offer assistance to decision makers to help in planning and scheduling tasks, determine the consequences of changes, provide support in the resolution of incidents, provide alternative plans, etc. As a case study to evaluate the behaviour of the techniques developed, this thesis focuses on problems related to container terminals. Container terminals generally serve as a transshipment zone between ships and land vehicles (trains or trucks). In (Henesey 2006a), it is shown how this transshipment market has grown rapidly. Container terminals are open systems with three distinguishable areas: the berth area, the storage yard, and the terminal receipt and delivery gate area. Each one presents different planning and scheduling problems to be optimized (Stahlbock and Voß 2008). For example, berth allocation, quay crane assignment, stowage planning, and quay crane scheduling must be managed in the berthing area; the container stacking problem, yard crane scheduling, and horizontal transport operations must be carried out in the yard area; and the hinterland operations must be solved in the landside area. Furthermore, dynamism is also present in container terminals. The tasks of the container terminals take place in an environment susceptible of breakdowns or incidences. For instance, a Quay Crane engine stopped working and needs to be revised, delaying this task one or two hours. Thereby, the robustness concept can be included in the scheduling techniques to take into consideration some incidences and return a set of robust schedules. In this thesis, we have developed a new domain-dependent planner to obtain more effi- cient solutions in the generic problem of reshuffles of containers. Planning heuristics and optimization criteria developed have been evaluated on realistic problems and they are applicable to the general problem of reshuffling in blocks world scenarios. Additionally, we have developed a scheduling model, using constructive metaheuristic techniques on a complex problem that combines sequences of scenarios with different types of resources (Berth Allocation, Quay Crane Assignment, and Container Stacking problems). These problems are usually solved separately and their integration allows more optimized solutions. Moreover, in order to address the impact and changes that arise in dynamic real-world environments, a robustness model has been developed for scheduling tasks. This model has been applied to metaheuristic schemes, which are based on genetic algorithms. The extension of such schemes, incorporating the robustness model developed, allows us to evaluate and obtain more robust solutions. This approach, combined with the classical optimality criterion in scheduling problems, allows us to obtain, in an efficient in way, optimized solution able to withstand a greater degree of incidents that occur in dynamic scenarios. Thus, a proactive approach is applied to the problem that arises with the presence of incidences and changes that occur in typical scheduling problems of a dynamic real world. / Rodríguez Molins, M. (2015). Optimization and Robustness in Planning and Scheduling Problems. Application to Container Terminals [Tesis doctoral no publicada]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/48545 / TESIS

Public transport network design deals with finding the most efficient network solution among a set of alternatives, that best satisfies the often-conflicting objectives of different network stakeholders like passengers and operators. Simulation-based Optimisation (SBO) is a discipline that solves optimisation problems by combining simulation and optimisation models. The former is used to evaluate the alternative solutions, while the latter searches for the optimal solution among them. A SBO model for designing public transport networks is developed in this dissertation. The context of the research is the MyCiTi Bus Rapid Transit (BRT) network in the City of Cape Town, South Africa. A multi-objective optimisation algorithm known as the Non-dominated Sorting Genetic Algorithm (NSGA-II) is integrated with Activity-based Travel Demand Model (ABTDM) known as the Multi-Agent Transport Simulation (MATSim). The steps taken to achieve the research objectives are first to generate a set of feasible network alternatives. This is achieved by manipulating the existing routes of the MyCiTi BRT with a computer based heuristic algorithm. The process is guided by feasibility conditions which guarantee that each network has routes that are acceptable for public transport operations. MATSim is then used to evaluate the generated alternatives, by simulating the daily plans of travellers on each network. A typical daily plan is a sequential ordering of all the trips made by a commuter within a day. Automated Fare Collection (AFC) data from the MyCiTi BRT was used to create this plan. Lastly, the NSGA-II is used to search for an efficient set of network solutions, also known as a Pareto set or a non-dominated set in the context of Multi-objective Optimisation (MOO). In each generation of the optimisation process, MATSim is used to evaluate the current solution. Hence a suitable encoding scheme is defined to enable a smooth iv translation of the solution between the NSGA-II and MATSim. Since the solution of multi-objective optimisation problems is a set of network solutions, further analysis is done to identify the best compromise solution in the Pareto set. Extensive computational testing of the SBO model has been carried out. The tests involve evaluating the computational performance of the model. The first test measures the repeatability of the model's result. The second computational test considers its performance relative to indicators like the hypervolume and spacing indicators as well as an analysis of the model's Pareto front. Lastly, a benchmarking of the model's performance when compared with other optimisation algorithms is carried out. After testing the so-called Simulation-based Transit Network Design Model (SBTNDM), it is then used to design pubic transport networks for the MyCiTi BRT. Two applications are considered for the model. The first application deals with the public transport performance of the network solutions in the Pareto front obtained from the SBTNDM. In this case study, different transport network indicators are used to measure how each solution performs. In the second scenario, network design is done for the 85th percentile of travel demand on the MyCiTi network over 12 months. The results show that the model can design robust transit networks. The use of simulation as the agency of optimisation of public transport networks represents the main innovation of the work. The approach has not been used for public transport network design to date. The specific contribution of this work is in the improved modelling of public transport user behaviour with Agent-based Simulation (ABS) within a Transit Network Design (TND) framework. This is different from the conventional approaches used in the literature, where static trip-based travel demand models like the four-step model have mostly been used. Another contribution of the work is the development of a robust technique that facilitates the simultaneous optimisation of network routes and their operational frequencies. Future endeavours will focus on extending the network design model to a multi-modal context.

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The subject of this doctoral thesis is the solution of logistics systems in the context of waste management. The work begins with an extensive research in the field of modelling various situations from the waste transportation chain. There are presented multiple types of practical tasks in the area of operation research applicable to waste management. Their possibilities of extension and modification are analysed for use by investors, technical services or waste collection service providers. An essential part of the work is the identification of critical parameters in the waste collection at the level of municipalities and micro-regions. Based on practical requirements, challenges related to the improvement of decision-making and planning systems are defined. The available techniques proved to be insufficient for practical problems. For the area of changes and designs of collection systems (design and modification of routes, choice of the vehicle fleet, collection plan, etc.) there are no procedures that would include a whole range of operating conditions and parameters. The boundary conditions of the task affecting fundamental requirements are highly variable. The thesis presents a comprehensive approach, which is divided into several phases. The preparation and analysis of input data focused mainly on the creation of transport infrastructure, allocation of waste collection containers and their pairing to the network, which also reduces the size of the task. Furthermore, a procedure for compliance with the rules of the road was designed using a penalty function, and an algorithm for defining imaginary edges was implemented, which will allow distinguishing the frequency of collection on selected network segments. To reduce the size of the task, a segment clustering algorithm was also designed, which will enable the calculation of the collection even for larger areas. Input parameters related to operating time and fullness of collection containers are elaborated in greater detail, as they most influence the results of the task. A great benefit is also the algorithm generating the initialization solution from historical routes. As part of the related publishing activities, environmental criteria were defined to evaluate global and local impacts of waste transportation and treatment. The outputs of the thesis are used primarily for the analysis of collection systems, to support the deployment of waste containers, planning collection routes, time schedules and dimensioning the size of the vehicle fleet. The proposed algorithms were tested in several case studies, which proved the broad applicability of a comprehensive tool in the field of waste logistics. Although the thesis is focused on modelling the collection of municipal waste, the usability of the implemented procedures is possible in other areas of waste management or other sectors.