Les entreprises de transport et de distribution sont confrontées à des difficultés d’exploitation liées à la taille et à la complexité de leur processus de livraison. Dans cette problématique, nous proposons une approche globale du Problème Général de Livraison (PGL).Au niveau méthodologique, c’est une approche hiérarchique (stratégique, tactique, opérationnelle) et structurée. Il s’agit de concevoir et d’exploiter un PGL en le décomposant en problèmes de livraisons élémentaires identifiés et le plus possible indépendants les uns des autres (problèmes de transport, de hubs, d’agences, de tournées...).Au niveau algorithmique, des modèles et algorithmes de résolution ont été proposés pour résoudre ces problèmes élémentaires de livraison dans la phase opérationnelle en tenant compte, en particulier, du nombre et de la capacité limités des moyens de transport.Au niveau applicatif, deux exemples réels sont traités : le système de livraison d’une entreprise de Vente à Distance et le système de livraison des casernes de pompiers du Nord de la France à partir de la pharmacie centrale de Lille / Transport and delivery companies are confronted by difficulties in their transportation process due to the scale and the complexity of their distribution process. In this context, we propose a comprehensive approach to General Delivery Problem (GDP). In terms of methodology, it is a hierarchical (strategic, tactical and operational) and structured approach. It consists of designing and decomposing the GDP into well identified basic delivery problems as independent as possible. These basic transport problems involve the problems about transportation, intermediate facility, agencies, routings, etc. At the algorithm level, models and solution algorithms have been proposed to solve these basic delivery problems in the operational phase, taking account in particular transportation restriction about the number and capacity of vehicles.At the application level, two real examples are discussed: one is the delivery system of a delivery company; the other one is the delivery system of the Regional Fire and Emergency Center in the north of France

Submitted by Aelson Maciera (aelsoncm@terra.com.br) on 2017-09-26T19:15:52Z No. of bitstreams: 1 DissCDAC.pdf: 10114021 bytes, checksum: b3e4f52846924539caadab8587fe2250 (MD5) / Approved for entry into archive by Ronildo Prado (bco.producao.intelectual@gmail.com) on 2018-01-26T18:36:20Z (GMT) No. of bitstreams: 1 DissCDAC.pdf: 10114021 bytes, checksum: b3e4f52846924539caadab8587fe2250 (MD5) / Approved for entry into archive by Ronildo Prado (bco.producao.intelectual@gmail.com) on 2018-01-26T18:36:39Z (GMT) No. of bitstreams: 1 DissCDAC.pdf: 10114021 bytes, checksum: b3e4f52846924539caadab8587fe2250 (MD5) / Made available in DSpace on 2018-01-26T18:42:45Z (GMT). No. of bitstreams: 1 DissCDAC.pdf: 10114021 bytes, checksum: b3e4f52846924539caadab8587fe2250 (MD5) Previous issue date: 2017-03-10 / Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq) / This work aims at treating the Dynamic Vehicle Allocation Problem (DVAP) in the context of the Brazilian Freight Transportation system. The problem consists of allocating empty vehicles to different terminals so as to attend the demand of freight transport during a predetermined planning horizon while maximizing the profit from these services. These type of decisions arise in customized freight transport services and in between-terminals operations of consolidation freight services. Given the size of the resulting models of real life problems confronted by third party logistics operators are large for using exact solution methods, heuristic methods have been used for giving good quality solution at the expense of optimality guarantee. In this context, the objective of this work is to contribute with solution methods that provide optimality guarantee or quality solution certificates for treating large-scale problems in reasonable computational times. The methods utilized are lagrangean relaxation, using subgradient optimization, and DantzigWolfe decomposition together with a lagrangian heuristic and factibilization method, respectively. Computational experiments are presented and analyzed for randomly generated instances and real-world instances from a brasilian freight operator. The latter method shows great potential for treating large-scale problems. / Este trabalho aborda o problema de Alocação Dinâmica de Veículos (PADV) no contexto de Transporte Rodoviário de Carga. O problema envolve alocar veículos de carga para atender a demanda de transporte de carga prevista entre terminais durante um horizonte de tempo multiperíodos e finito. O objetivo e maximizar o lucro gerado pelos serviços completados. Este tipo de decisões surge nos serviços de transporte de carga de lotação e na parcela de transporte de transferência dos serviços de transporte de carga consolidada. Dado que o tamanho dos problemas que enfrentam as transportadoras logísticas sÃo consideravelmente grandes parase resolver com métodos exatos em tempos computacionais aceitáveis, tem-se utilizado métodos heurísticos para dar boas soluções sem garantia de otimalidade mas em tempos toleráveis a estes problemas. Neste contexto, pretende-se contribuir com métodos de solução que proporcionem garantia de otimalidade e/ou boas soluções aproximadas, acompanhadas de certificados de otimalidade ou de qualidade de solução, para tratar problemas de porte em tempos razoáveis. Os métodos propostos estao baseados em relaxação lagrangiana, utilizando o método de otimização do subgradiente, e na decomposto de Dantzig Wolfe, utilizando a técnica de geração de colunas, além de heurísticas lagrangianas e de factibilização acopladas nestes métodos. Experimentos computacionais usando instâncias geradas aleatoriamente e baseados em dados reais de transportadoras brasileiras sao apresentados e analisados, para as duas abordagens, mostrando seus potenciais de aplicação pratica, principalmente para problemas de grande porte.

Made available in DSpace on 2016-08-17T14:53:08Z (GMT). No. of bitstreams: 1 Victor Hugo Barros Silva.pdf: 4177386 bytes, checksum: 324ffa71e5b64047e7a54ab199bb9241 (MD5) Previous issue date: 2010-03-22 / Conselho Nacional de Desenvolvimento Científico e Tecnológico / The problem of allocating berth positions for vessels in tidal grain port terminals is discussed in this work. A berth defines a specific location alongside a quay where a ship loader is available for loading or unloading vessels, accommodating only one vessel at time. In tidal ports, draft conditions depend on high tide conditions, since available depth under the low tide is not adequate to the movement of ships. Some port terminals at the port complex of São Luís, Maranhão, are associated to important transnational enterprises which maintain a strong control over the stock level of their goods. Since the stock level sometimes depends on a continuous process of consumption or production of grains, the decision making of loading or unloading vessels must contemplate the amount of the grain stored in the port yards. Therefore, a basic criterion for decision making is to give priority to the vessels related to the most critical grain stock level. This paper presents two integer linear programming models based on the transportation problem to represent the discussed problem. Some problem instances could be solved by a commercial solver. As an alternative to larger instances, which require large running time, an implementation of Simulated Annealing (SA) and the algorithm known as Population Training Algorithm for Linear Programming (PTA/LP) are used to solve the problem. / O Problema de Alocação de Berços em Portos Graneleiros com Restrições de Estoque e Condições Favoráveis de Maré é abordado neste trabalho. Um berço define um local especifico ao longo do cais onde um carregador de navio está disponível para carregar ou descarregar navios, acomodando apenas um navio por vez. Em portos que sofrem a influência da variação das marés, as condições de navegação dependem de condições favoráveis de maré, uma vez que a profundidade na maré baixa restringe a movimentação de navios. Alguns terminais no complexo portuário de São Luís, Maranhão, estão associados a importantes empresas multinacionais que mantêm um forte controle sobre os níveis de estoque de seus produtos. Uma vez que o nível de estoque, por vezes, depende de um processo contínuo de consumo ou produção de granéis, a tomada de decisão de carregar ou descarregar navios deve levar em conta as cargas armazenadas nos pátios do porto. Desta forma, um critério básico para tomadas de decisão é dar prioridade aos navios relacionada aos níveis mais críticos de estoque. Este trabalho apresenta dois modelos de programação linear baseado no problema de transporte para representar o problema abordado. Algumas instâncias do problema puderam ser resolvidas por um solver comercial. Como alternativa suas instâncias maiores, que exigem grande tempo de execução, uma implementação do Simulated Annealing (SA) e do algoritmo conhecido como Algoritmo de Treinamento Populacional para Programação Linear (ATP/PL) são empregadas para resolução do problema.

Les problèmes d’optimisation combinatoire sont généralement réputés NP-difficiles, donc il n’y a pas d’algorithmes efficaces pour les résoudre. Afin de trouver des solutions optimales locales ou réalisables, on utilise souvent des heuristiques ou des algorithmes approchés. Les dernières décennies ont vu naitre des méthodes approchées connues sous le nom de métaheuristiques, et qui permettent de trouver une solution approchées. Cette thèse propose de résoudre des problèmes d’optimisation déterministe et stochastique à l’aide de métaheuristiques. Nous avons particulièrement étudié la méthode de voisinage variable connue sous le nom de VNS. Nous avons choisi cet algorithme pour résoudre nos problèmes d’optimisation dans la mesure où VNS permet de trouver des solutions de bonne qualité dans un temps CPU raisonnable. Le premier problème que nous avons étudié dans le cadre de cette thèse est le problème déterministe de largeur de bande de matrices creuses. Il s’agit d’un problème combinatoire difficile, notre VNS a permis de trouver des solutions comparables à celles de la littérature en termes de qualité des résultats mais avec temps de calcul plus compétitif. Nous nous sommes intéressés dans un deuxième temps aux problèmes de réseaux mobiles appelés OFDMA-TDMA. Nous avons étudié le problème d’affectation de ressources dans ce type de réseaux, nous avons proposé deux modèles : Le premier modèle est un modèle déterministe qui permet de maximiser la bande passante du canal pour un réseau OFDMA à débit monodirectionnel appelé Uplink sous contraintes d’énergie utilisée par les utilisateurs et des contraintes d’affectation de porteuses. Pour ce problème, VNS donne de très bons résultats et des bornes de bonne qualité. Le deuxième modèle est un problème stochastique de réseaux OFDMA d’affectation de ressources multi-cellules. Pour résoudre ce problème, on utilise le problème déterministe équivalent auquel on applique la méthode VNS qui dans ce cas permet de trouver des solutions avec un saut de dualité très faible. Les problèmes d’allocation de ressources aussi bien dans les réseaux OFDMA ou dans d’autres domaines peuvent aussi être modélisés sous forme de problèmes d’optimisation bi-niveaux appelés aussi problèmes d’optimisation hiérarchique. Le dernier problème étudié dans le cadre de cette thèse porte sur les problèmes bi-niveaux stochastiques. Pour résoudre le problème lié à l’incertitude dans ce problème, nous avons utilisé l’optimisation robuste plus précisément l’approche appelée « distributionnellement robuste ». Cette approche donne de très bons résultats légèrement conservateurs notamment lorsque le nombre de variables du leader est très supérieur à celui du suiveur. Nos expérimentations ont confirmé l’efficacité de nos méthodes pour l’ensemble des problèmes étudiés. / Combinatorial optimization problems are generally NP-hard problems, so they can only rely on heuristic or approximation algorithms to find a local optimum or a feasible solution. During the last decades, more general solving techniques have been proposed, namely metaheuristics which can be applied to many types of combinatorial optimization problems. This PhD thesis proposed to solve the deterministic and stochastic optimization problems with metaheuristics. We studied especially Variable Neighborhood Search (VNS) and choose this algorithm to solve our optimization problems since it is able to find satisfying approximated optimal solutions within a reasonable computation time. Our thesis starts with a relatively simple deterministic combinatorial optimization problem: Bandwidth Minimization Problem. The proposed VNS procedure offers an advantage in terms of CPU time compared to the literature. Then, we focus on resource allocation problems in OFDMA systems, and present two models. The first model aims at maximizing the total bandwidth channel capacity of an uplink OFDMA-TDMA network subject to user power and subcarrier assignment constraints while simultaneously scheduling users in time. For this problem, VNS gives tight bounds. The second model is stochastic resource allocation model for uplink wireless multi-cell OFDMA Networks. After transforming the original model into a deterministic one, the proposed VNS is applied on the deterministic model, and find near optimal solutions. Subsequently, several problems either in OFDMA systems or in many other topics in resource allocation can be modeled as hierarchy problems, e.g., bi-level optimization problems. Thus, we also study stochastic bi-level optimization problems, and use robust optimization framework to deal with uncertainty. The distributionally robust approach can obtain slight conservative solutions when the number of binary variables in the upper level is larger than the number of variables in the lower level. Our numerical results for all the problems studied in this thesis show the performance of our approaches.

This thesis will provide knowledge on how to maintain a well developed flow of material while at the same time finding an optimal level of capacities for buffers. Simultaneously, aspects that allow for positive sustainability practices will be regarded.  Buffers have a considerable impact on the performance of a production system. However, the process of optimizing buffers remains a complex task, and is therefore in need of further research. Through a thorough data collection process, simulation modeling and Multi-objective Optimization, the authors will present evidence-based recommendations for managing buffers in an optimal manner. The case company currently has two buffer zones that are to be investigated if they could be improved by finding an optimal capacity level. The current flow of material consists of certain variations in the components that will be taken into consideration, some variations need further investigation in order to be representative and applicable to this study. By applying amongst other things, Lean concepts, Gemba walks, simulation modeling, interviews and knowledge within the specific field of buffer optimization, the authors were able to provide evidence-based recommendations. These recommendations both take into account optimal buffer capacities as well as brief sustainability and economical aspects. The authors have found that one buffer zone has the potential of being removed, which will contribute to positive environmental aspects. However, if this solution is to be applied, the need of planning and managing the distribution of components is required.  Another buffer zone has been investigated by applying the concept of Multi-objective Optimization, where the objectives are to maintain high throughput while minimizing the buffer capacities. The optimization procedure generated a decrease in buffer capacities in the zone by a total of 35%. This newly acquired space can either be used for other manufacturing processes, or be discontinued, which would decrease the energy consumption and positively affect the sustainability aspect.

[pt] A matriz brasileira de transporte retrata a dominância rodoviária sobre os demais modais, na movimentação de cargas no país. O aumento da eficiência operacional e redução de custos é fator que pode elevar a participação e competitividade dos trens nesse contexto. A aplicação de técnicas de otimização no processo de dimensionamento e planejamento operacional da frota de locomotivas possui grande potencial de economia de recursos, principalmente devido aos seus elevados custos de aquisição e manutenção. O presente trabalho apresenta uma metodologia para obtenção de uma solução exata para um horizonte mensal de planejamento, aproveitando se do caráter cíclico da grade de formação dos trens de carga geral, para definir o tamanho ótimo da frota necessário ao seu adequado funcionamento. A metodologia, implementada em linguagem Python e aplicada em um cenário de uma grade conhecida, teve sua frota resultante comparada com o dimensionamento manual realizado em uma concessionária brasileira e foi capaz de indicar a redução de 2 locomotivas no planejamento de frota. Associada a esta redução, a economia de capital estimada seria entre 400 mil reais e 20 milhões de reais, para o cenário conservador de economia dos gastos de manutenção e para o cenário mais otimista evitando a aquisição de novas locomotivas. Além da redução de frota e aumento na competitividade tarifária dos trens de carga geral, a metodologia cria, por meio de critérios científicos, diretrizes objetivas para o processo de dimensionamento e planejamento da frota de locomotivas, em substituição ao processo empírico atualmente aplicado na referida concessionária. / [en] The Brazilian transport matrix presents the road dominance over other modes in the movement of cargo in the country. The increase in operational efficiency and cost reduction is a factor that can increase the participation and competitiveness of trains in this context. The application of optimi zation techniques in the process of dimensioning and operational planning of the locomotive fleet has great potential for saving resources, mainly due to its high acquisition and maintenance costs. This work presents a methodology to obtain an exact soluti on for a monthly planning horizon, taking advantage of the cyclical character of the general freight trains timetables and defining the optimum fleet size necessary for its proper functioning. The methodology, implemented in Python language and applied in a scenario of a defined timetable had its resulting fleet compared with the manual sizing process carried out in a Brazilian dealership and was able to indicate the reduction of 2 locomotives in the fleet planning. Associated with this reduction, the est imated capital savings would be between 400 thousand reais and 20 million reais, for the conservative scenario of savings in maintenance costs and for the more optimistic scenario avoiding the acquisition of new locomotives. In addition to reducing the fleet and increasing the tariff competitiveness of general freight trains, the methodology creates, through scientific criteria, objective guidelines for the process of dimensioning and planning the locomotive fleet, replacing the empirical process currently applied in the aforementioned concessionaire.

Text in Afikaans / In this thesis contributions to the solution of the generalised knapsack problem are given and discussed. Attention is given to problems with functions that are calculable but not necessarily in a closed form. Algorithms and test problems can be used for problems with closed-form functions as well. The focus is on the development of good heuristics and not on exact algorithms. Heuristics must be investigated and good test problems must be designed. A measure of convexity for convex functions is developed and adapted for concave functions. A test problem generator makes use of this measure of convexity to create challenging test problems for the concave, convex and mixed knapsack problems. Four easy-to-interpret characteristics of an S-function are used to create test problems for the S-shaped as well as the generalised knapsack problem. The in uence of the size of the problem and the funding ratio on the speed and the accuracy of the algorithms are investigated. When applicable, the in uence of the interval length ratio and the ratio of concave functions to the total number of functions is also investigated. The Karush-Kuhn-Tucker conditions play an important role in the development of the algorithms. Suf- cient conditions for optimality for the convex knapsack problem with xed interval lengths is given and proved. For the general convex knapsack problem, the key theorem, which contains the stronger necessary conditions, is given and proved. This proof is so powerful that it can be used to proof the adapted key theorems for the mixed, S-shaped and the generalised knapsack problems as well. The exact search-lambda algorithm is developed for the concave knapsack problem with functions that are not in a closed form. This algorithm is used in the algorithms to solve the mixed and S-shaped knapsack problems. The exact one-step algorithm is developed for the convex knapsack problem with xed interval length. This algorithm is O(n). The general convex knapsack problem is solved by using the pivot algorithm which is O(n2). Optimality cannot be proven but in all cases the optimal solution was found and for all practical reasons this problem will be considered as being concluded. A good heuristic is developed for the mixed knapsack problem. Further research can be done on this heuristic as well as on the S-shaped and generalised knapsack problems. / Mathematical Sciences / D. Phil. (Operasionele Navorsing)

本研究探討長期投資人之最適資產配置問題，並著重於通貨膨脹風險之分析。第一部份討論確定提撥退休金制度下，機構投資人或高所得自然人如何擬定投資策略規避通貨膨脹風險，達到極大化期末財富效用期望值。此研究擴展Battocchio與Menoncin (2004)所建構資產模型，不僅探討市場風險，亦考量通貨膨脹不確定性與基金費用誘因、下方風險保護兩機制，研究對資產配置行為之影響，並依動態規劃方法求得投資策略公式解。第二部份則強調下方風險之重要性，檢視在最低保證收益下，長期投資人跨期資產配置之財富管理議題，並回顧Deelstra et al.(2003)之模型架構，依平賭方法求得投資策略公式解，研究結果顯示基金投資策略可表示為最適CRRA(γ,T)型態共同基金與最低收益避險之組合。另一方面，如何估計通貨膨脹風險亦為本文強調之重點。Campbell和Viceira (2001)首次納入通貨膨脹風險並探討跨期投資議題，結論市場缺乏通貨膨脹連動投資標的時，投資人將減碼長期債持有比例。Brennan和Xia (2002)假設通貨膨脹率服從Ornstein-Uhlenbeck過程，結論投資人之避險需求隨持有債券到期日與投資期限改變。但以上結論未將通貨膨脹學習機制納入模型，因此，在第三部份提出依學習機制修正之投資策略可顯著增加財富效用，並分析在不同參數設定下，學習機制對於期末財富效用之影響。 / In this study, we study three essays of asset allocation problem for long term investors, which means that in this discourse we emphasis the importance of inflation risk. In the first topic, we derive the dynamic optimal investment strategy of the defined contribution pension schemes which include two mechanisms of partial floor protection and incentive fees and their benchmarks. We find investors should hold high proportion of stock index fund to hedge the inflation risk; moreover, the ratio of incentive fees to the setting of benchmark will change the optimal investment trend of underlying assets. In the second topic, we introduce the optimal investment portfolio with minimum guarantees and show that the fund manager should adjust the optimal weights of underlying assets with the ratio of the guarantee fund's value to the value of fund. Finally, this work focuses on how to precisely predict the dynamics of inflation rate. We apply learning method to adjust the prediction of inflation process and we use numerical analysis to study the effect of learning mechanism under different parameter setting.

Text in Afikaans / In this thesis contributions to the solution of the generalised knapsack problem are given and discussed. Attention is given to problems with functions that are calculable but not necessarily in a closed form. Algorithms and test problems can be used for problems with closed-form functions as well. The focus is on the development of good heuristics and not on exact algorithms. Heuristics must be investigated and good test problems must be designed. A measure of convexity for convex functions is developed and adapted for concave functions. A test problem generator makes use of this measure of convexity to create challenging test problems for the concave, convex and mixed knapsack problems. Four easy-to-interpret characteristics of an S-function are used to create test problems for the S-shaped as well as the generalised knapsack problem. The in uence of the size of the problem and the funding ratio on the speed and the accuracy of the algorithms are investigated. When applicable, the in uence of the interval length ratio and the ratio of concave functions to the total number of functions is also investigated. The Karush-Kuhn-Tucker conditions play an important role in the development of the algorithms. Suf- cient conditions for optimality for the convex knapsack problem with xed interval lengths is given and proved. For the general convex knapsack problem, the key theorem, which contains the stronger necessary conditions, is given and proved. This proof is so powerful that it can be used to proof the adapted key theorems for the mixed, S-shaped and the generalised knapsack problems as well. The exact search-lambda algorithm is developed for the concave knapsack problem with functions that are not in a closed form. This algorithm is used in the algorithms to solve the mixed and S-shaped knapsack problems. The exact one-step algorithm is developed for the convex knapsack problem with xed interval length. This algorithm is O(n). The general convex knapsack problem is solved by using the pivot algorithm which is O(n2). Optimality cannot be proven but in all cases the optimal solution was found and for all practical reasons this problem will be considered as being concluded. A good heuristic is developed for the mixed knapsack problem. Further research can be done on this heuristic as well as on the S-shaped and generalised knapsack problems. / Mathematical Sciences / D. Phil. (Operasionele Navorsing)