Production and Delivery (Optimization of production system and reliability)

This thesis is done to solve two issues for Sayid Paper Mill Ltd Pakistan. Section one deals with a practical problem arise in SPM that is cutting a given set of raw paper rolls of known length and width, and a set of product paper rolls of known length (equal to the length of raw paper rolls) and width, practical cutting constraints on a single cutting machine, according to demand orders for all customers. To solve this problem requires to determine an optimal cutting schedule to maximize the overall cutting process profitability while satisfying all demands and cutting constraints. The aim of this part of thesis is to develop a mathematical model which solves this problem.Second section deals with a problem of delivering final product from warehouse to different destinations by finding shortest paths. It is an operational routing problem to decide the daily routes for sending trucks to different destination to deliver their final product. This industrial problem is difficult and includes aspect such as delivery to a single destination and multiple destinations with limited resources. The aim of this part of thesis is to develop a process which helps finding shortest path.

Optimization of cable cycles : a trade-off between reliability and cost

This paper elaborates the routing of cable cycle through available routes in a building in order to link a set of devices, in a most reasonable way. Despite of the similarities to other NP-hard routing problems, the only goal is not only to minimize the cost (length of the cycle) but also to increase the reliability of the path (in case of a cable cut) which is assessed by a risk factor. Since there is often a trade-off between the risk and length factors, a criterion for ranking candidates and deciding the most reasonable solution is defined. A set of techniques is proposed to perform an efficient and exact search among candidates. A novel graph is introduced to reduce the search-space, and navigate the search toward feasible and desirable solutions. Moreover, admissible heuristic length estimation helps to early detection of partial cycles which lead to unreasonable solutions. The results show that the method provides solutions which are both technically and financially reasonable. Furthermore, it is proved that the proposed techniques are very efficient in reducing the computational time of the search to a reasonable amount.

Um algoritmo híbrido para o problema de roteamento de veículos com frotas heterogêneas

This paper aims to propose a hybrid meta-heuristics for the Heterogeneous Fleet Vehicle Routing Problem (HVRP), which is a combinatorial optimization problem NP-hard, and is characterized by the use of a limited fleet consists of different vehicles with different capacities. The hybrid method developed makes use of a memetic algorithm associated with the component optimizer Vocabulary Building. The resulting hybrid meta-heuristic was implemented in the programming language C + + and computational experiments generated good results in relation to meta-heuristic applied in isolation, proving the efficiency of the proposed method.

Metaheurísticas evolutivas para o problema de roteamento de unidades móveis de pistoneio

This paper presents metaheuristic strategies based on the framework of evolutionary algorithms (Genetic and Memetic) with the addition of Technical Vocabulary Building for solving the Problem of Optimizing the Use of Multiple Mobile Units Recovery of Oil (MRO units). Because it is an NP-hard problem, a mathematical model is formulated for the problem, allowing the construction of test instances that are used to validate the evolutionary metaheuristics developed

Análise do uso de SIG no roteamento dos veículos de coleta de resíduos sólidos domiciliares

Relata-se neste trabalho, a análise do uso de um Sistema de Informação Geográfica - SIG como ferramenta para roteirização de veículos de coleta de resíduos sólidos domiciliares. O software utilizado foi o TransCAD, versão 3.2, que permite desenvolver rotas utilizando algoritmos que incluem o procedimento de roteirização em arco. O objetivo é minimizar a extensão total a ser percorrida pelos veículos coletores. O estudo de caso foi realizado na cidade de Ilha Solteira - SP. Os dados coletados e os resultados obtidos pelo TransCAD foram processados no software Microsoft Excel. Os resultados obtidos demonstraram reduções percentuais de até 41% na distância total percorrida e de 68% no tempo total de percurso em relação ao serviço atual.

Um estudo algorítmico da programação da intervenção de sondas de produção

This work approaches the Scheduling Workover Rigs Problem (SWRP) to maintain the wells of an oil field, although difficult to resolve, is extremely important economical, technical and environmental. A mathematical formulation of this problem is presented, where an algorithmic approach was developed. The problem can be considered to find the best scheduling service to the wells by the workover rigs, taking into account the minimization of the composition related to the costs of the workover rigs and the total loss of oil suffered by the wells. This problem is similar to the Vehicle Routing Problem (VRP), which is classified as belonging to the NP-hard class. The goal of this research is to develop an algorithmic approach to solve the SWRP, using the fundamentals of metaheuristics like Memetic Algorithm and GRASP. Instances are generated for the tests to analyze the computational performance of the approaches mentioned above, using data that are close to reality. Thereafter, is performed a comparison of performance and quality of the results obtained by each one of techniques used

Um estudo algorítmico de problemas logísticos na indústria de petróleo e gás natural

This work consists on the study of two important problems arising from the operations of petroleum and natural gas industries. The first problem the pipe dimensioning problem on constrained gas distribution networks consists in finding the least cost combination of diameters from a discrete set of commercially available ones for the pipes of a given gas network, such that it respects minimum pressure requirements at each demand node and upstream pipe conditions. On its turn, the second problem the piston pump unit routing problem comes from the need of defining the piston pump unit routes for visiting a number of non-emergent wells in on-shore fields, i.e., wells which don t have enough pressure to make the oil emerge to surface. The periodic version of this problem takes into account the wells re-filling equation to provide a more accurate planning in the long term. Besides the mathematical formulation of both problems, an exact algorithm and a taboo search were developed for the solution of the first problem and a theoretical limit and a ProtoGene transgenetic algorithm were developed for the solution of the second problem. The main concepts of the metaheuristics are presented along with the details of their application to the cited problems. The obtained results for both applications are promising when compared to theoretical limits and alternate solutions, either relative to the quality of the solutions or to associated running time

Análise de uso de SIG no sistema de coleta de resíduos sólidos domiciliares em uma cidade de pequeno porte

Pós-graduação em Engenharia Civil - FEIS

Otimização de cobertura, consumo de energia, roteamento e agregação de dados em rede de sensores sem fio utilizando algoritmos genéticos e lógica fuzzy

As Redes de Sensores Sem Fio possuem capacidades limitadas de processamento, armazenamento, comunicação (largura de banda) e fonte de energia, além de possuírem características e requisitos básicos de uma RSSF como: necessidade de se auto-organizar, comunicação com difusão de curto alcance e roteamento com múltiplos saltos. Neste trabalho é proposto uma ferramenta que otimize o posicionamento e os pacotes entregues através do uso de Algoritmo Genético (AG). Para solucionar o problema de roteamento que melhore o consumo de energia e maximize a agregação de dados é proposto a utilização de lógica fuzzy no protocolo de roteamento Ad hoc Ondemand Distance Vector (AODV). Esta customização é intitulada AODV – Fuzzy for Wireless Sensor Networks (AODV-FWSN). Os resultados mostram que a solução proposta é eficiente e consegue prolongar a vida útil da RSSF e melhorar a taxa de entrega de dados quando comparado com soluções similares.

Uma proposta de resolução para problemas de roteirização de veículos baseada no algoritmo genético

The vehicle routing problem is to nd a better route to meet a set of customers who are geographically dispersed using vehicles that are a central repository to which they return after serving customers. These customers have a demand that must be met. Such problems have a wide practical application among them we can mention: school transport, distribution of newspapers, garbage collection, among others. Because it is a classic problem as NP-hard, these problems have aroused interest in the search for viable methods of resolution. In this paper we use the Genetic Algorithm as a resolution

Rerouting Schemes for Dynamic Traffic Grooming in Optical WDM Mesh Networks

Traffic grooming in optical WDM mesh networks is a two-layer routing problem to effectively pack low-rate connections onto high-rate lightpaths, which, in turn, are established on wavelength links. In this work, we employ the rerouting approach to improve the network throughput under the dynamic traffic model. We propose two rerouting schemes, rerouting at lightpath level (RRAL) and rerouting at connection level (RRAC). A qualitative comparison is made between RRAL and RRAC. We also propose the critical-wavelength-avoiding one-lightpath-limited (CWA-1L) and critical-lightpath-avoiding one-connection-limited (CLA-1C) rerouting heuristics, which are based on the two rerouting schemes respectively. Simulation results show that rerouting reduces the connection blocking probability significantly.

Progetto e sviluppo di un algoritmo per la pianificazione ottimizzata della distribuzione con viaggi sincronizzati

Il lavoro di tesi svolto riguarda la progettazione e lo sviluppo di un algoritmo per la pianificazione ottimizzata della distribuzione con viaggi sincronizzati; il metodo sviluppato è un algoritmo mateuristico. I metodi mateuristici nascono dall’integrazione di algoritmi esatti, utilizzati all’interno di un framework metaeuristico, scelto come paradigma di soluzione del problema. La combinazione di componenti esatte e algoritmi metaeuristici ha lo scopo di sfruttare i vantaggi di entrambi gli approcci: grazie all'uso di componenti esatte, è possibile operare in modo efficace e di concentrarsi su alcuni dei vincoli del problema, mentre, con l'utilizzo di un framework metaeuristico, si può efficacemente esplorare grandi aree dello spazio di ricerca in tempi accettabili. Il problema analizzato nel lavoro di tesi è un problema di trasporto, ovvero il Vehicle Routing Problem con finestre temporali e vincoli di sincronizzazione a coppie (VRPTWPS). Il problema richiede di individuare un piano di organizzazione ottimizzato per i viaggi di consegna merci presso un insieme di clienti; ogni cliente richiede che la consegna avvenga all’interno di orari predefiniti; un sottoinsieme di essi richiede, inoltre, che la consegna venga effettuata con la presenza di esattamente due addetti. La presenza di quest’ultimo vincolo richiede, dunque, che due incaricati, indipendentemente dai viaggi di visita che questi effettuano, si incontrino presso uno stesso cliente nello stesso istante. Il vincolo di sincronizzazione rende il problema difficile da risolvere in maniera ottimizzata con i tradizionali metodi di ricerca locale; da ciò nasce l’uso dei metodi mateuristici per la risoluzione ottimizzata del problema. Grazie all’utilizzo di algoritmi esatti, i metodi mateuristici riescono a trattare in maniera più efficace alcuni vincoli dei problemi da risolvere.

Progettazione e sviluppo di software di supporto alla logistica dei trasporti.

Uno dei problemi più diffusi, nell'ambito della logistica, è rappresentato dai costi di trasporto. La gestione dei flussi merci, l'approvvigionamento dei clienti, e la relativa pianifcazione della movimentazione dei veicoli, hanno incidenze notevoli sui costi di gestione aziendali, i quali vengono stimati mediamente nel 45% dei costi logistici. A ragione di questo, sono sempre di più le aziende che ricorrono all'impiego di uffici dedicati alla pianifcazione delle consegne e la gestione dei trasporti in generale. Sebbene le voci di bilancio relative al trasporto raggiungano cifre rilevanti, fno al 4% del fatturato annuo, il tema della pianifcazione viene spesso sottovalutato. Infatti la soluzione a problemi di pianifcazione e monitoraggio dei costi, è spesso demandata a procedure manuali senza supporto informatico. Nasce da qui l'esigenza di proporre uno strumento informatico che supporti gli addetti preposti alla pianifcazione, sviluppando un sistema che copra esigenze di pianifcazione dei viaggi, controllo e consuntivazione dei costi di trasporto, e monitoraggio dei mezzi in tempo reale. La proposta di Gesp srl, Geographic Information Systems, azienda italiana che opera da anni nel campo delle applicazioni software geo-spaziali, prende il nome di Nuovo Sistema Trasporti, o più semplicemente, NST. In quest'ambito prende corpo questa tesi, la quale si pone l'obiettivo di illustrare le fasi di nascita, analisi, progettazione e sviluppo di un software generico per il supporto alla logistica. Saranno così analizzati: le problematiche affrontate nella fase di defnizione, e kick-off (avvio), del progetto, il problema del routing, o Vehicle Routing Problem e le tecniche di Ricerca Operativa che vengono applicate per la sua risoluzione; le moderne metodologie di gestione e sviluppo di un software; l'architettura e le tecnologie impiegate per la distribuzione dell'applicativo.

Many-core Algorithms for Combinatorial Optimization

Combinatorial Optimization is becoming ever more crucial, in these days. From natural sciences to economics, passing through urban centers administration and personnel management, methodologies and algorithms with a strong theoretical background and a consolidated real-word effectiveness is more and more requested, in order to find, quickly, good solutions to complex strategical problems. Resource optimization is, nowadays, a fundamental ground for building the basements of successful projects. From the theoretical point of view, Combinatorial Optimization rests on stable and strong foundations, that allow researchers to face ever more challenging problems. However, from the application point of view, it seems that the rate of theoretical developments cannot cope with that enjoyed by modern hardware technologies, especially with reference to the one of processors industry. In this work we propose new parallel algorithms, designed for exploiting the new parallel architectures available on the market. We found that, exposing the inherent parallelism of some resolution techniques (like Dynamic Programming), the computational benefits are remarkable, lowering the execution times by more than an order of magnitude, and allowing to address instances with dimensions not possible before. We approached four Combinatorial Optimization’s notable problems: Packing Problem, Vehicle Routing Problem, Single Source Shortest Path Problem and a Network Design problem. For each of these problems we propose a collection of effective parallel solution algorithms, either for solving the full problem (Guillotine Cuts and SSSPP) or for enhancing a fundamental part of the solution method (VRP and ND). We endorse our claim by presenting computational results for all problems, either on standard benchmarks from the literature or, when possible, on data from real-world applications, where speed-ups of one order of magnitude are usually attained, not uncommonly scaling up to 40 X factors.