This thesis is continuation of the bachelor thesis "Model of delivery routes and placement logistics centers with opportunities of their optimization". It is about distribution problems and specifically a vehicle routing problem. The aim of this thesis is finding a solution of the vehicle routing problem which will be used repeatedly in the firm. The main task is achieving the lowest costs (total kilometers) with maximum utilization of vehicle capacity; in such conditions that all requirements of logistics centers will be satisfied and maximal capacity of vehicle will be tolerated. For calculation was used a solver Gurobi 6.0.3 in system MPL for Windows 4.2, which won't, however, provide the optimal solution and problem solving takes too long time. Next for calculation was used heuristics insert method and is written by VBA (Visual Basic for Applications) in MS Excel. Finally, there is a comparison of these methods with the original solution of the vehicle routing plan and solution of the bachelor thesis. Then the computational experiment was done, which tested effect to result, if other distribution center (starting point) will be bulit. The computational experiment was consist from heuristic insert method, solver Gurobi and heuristic saving algorithm from bachelor thesis.

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.

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.

The main aim of this thesis is flow shop and job shop scheduling problem in logistics warehouses. Managing and scheduling works is currently often problem. There is no simple solution due to complexity of this problem. This problem must be resolved because of a lack efficiency of work with a higher load such as during the christmas holidays. This paper describes the methods used to solve this problem focusing mainly on the use of search algorithms, evolutionary algorithms, specifically grammar guided genetic programming. This paper describes the problem of job shop scheduling on a simple theoretical example. The implemented algorithm for solving this problem was subjected to tests inspired on data from real warehouse, as well as synthetically created tests with more jobs and a greater number of workers. Synthetic tests were generated randomly. All tests were therefore run several times and the results were averaged. In conclusion of this work are presented the results of the algorithm and the optimum parameter settings for different sizes of problems and requirements for the solution. Genetic algorithm has been extended to calculate fitness of individuals with regard to number of collisions, extended to use priority rules during run of evolution, and some parts of algorithm was parallelized.