[pt] O aumento da produção de petróleo brasileiro e o consequente aumento na demanda por transporte marítimo levaram a PETROBRAS a buscar ferramentas para aumentar a eficiência de seu transporte marítimo. Neste sentido, a atividade de programação de navios busca alocar os navios a um conjunto de cargas definido a priori, respeitando as restrições comerciais e operacionais, a fim de transportá-las com o menor custo possível. Com o intuito de auxiliar o programador nesta atividade, esta dissertação propõe um sistema de suporte à decisão (SSD) baseado em otimização para a programação de navios. O SSD proposto foi desenhado especificamente para a atividade de longo curso de navios de petróleo da PETROBRAS, sendo este gerado a partir da adaptação de modelos disponíveis na literatura acadêmica. Os testes comparativos realizados com o protótipo do SSD na atividade de longo curso de navios de petróleo mostraram que a ferramenta tem um significativo potencial de redução de custo. O SSD proposto se apresentou como uma opção viável para auxiliar a programação de navios da companhia na busca pela redução de custos de transporte marítimo. / [en] The increasing production of Brazilian oil and the consequent increase in the demand for shipping, led PETROBRAS to seek tools to increase the efficiency of its shipping. In this sense, the activity of ship scheduling seeks to assign vessels to a set of cargos, respecting business and operational restrictions in order to transport them with the lowest possible cost. To assist the ship scheduling planner in this activity, this dissertation proposes an optimization based decision support system (DSS) for ship scheduling. The proposed DSS was designed specifically for the long-term tanker scheduling activity at PETROBRAS and it was implemented based on models available in the academic literature. The comparative tests using the DSS prototype proposed in this dissertation showed that it has a potential for significant cost reduction. The proposed DSS was considered a viable tool to assist the ship scheduling planners in reducing shipping costs.

No description available.

Este trabalho trata de um problema de programação da produção em fundições de pequeno porte, que consiste em programar as ligas que devem ser produzidas em cada período do planejamento e como tais ligas devem ser usadas para a produção de itens sob encomenda, de modo que atrasos e custos operacionais sejam minimizados. Devido à certa incerteza nos dados do problema, a estratégia de horizonte rolante foi empregada. Este problema é representado por um modelo matemático de programação linear inteira mista. Neste trabalho foi desenvolvida uma heurística do tipo residual para obter uma boa solução inteira factível do problema, partindo da solução contínua encontrada pelos métodos relaxe-e-fixe e busca local / This work addresses a planning production problem that arises in small market-driven foundries, which consists of programming a number of alloys that have to be produced in each period of the planning horizon and how these alloys should be used to producing ordered items, in such way that delays and operational costs are minimized. Due to uncertainties in the problem data, the strategy of rolling horizon was used. This problem is modeled as a mixed integer linear programe. In this work we developed a residual typed heuristic in order to obtain a good feasible integer solution of the problem, which are built from the continuous solution found by relax-and-fix and local search methods. Keywords: Lot-sizing problems, mixed integer linear programming, production planning in foundries

A localização de fábricas, fornecedores e/ou CDs é um problema de grande complexidade, principalmente em empresas com operações internacionais. Na literatura mundial são poucos os modelos desenvolvidos que tratam da localização de instalações em escala global. Este trabalho propõe um modelo de Programação Linear Inteira Mista que soluciona o problema minimizando os custos logísticos (custos fixos, custos de transferência, custos de distribuição, impostos não recuperáveis, estoques, take-or-pay, matéria-prima e custos de agregação de valor e transbordo) levando em consideração vários elos da cadeia de suprimentos. Como principais contribuições do modelo citam-se a inclusão de benefícios fiscais em transações internacionais, tais como o drawback, o cálculo pioneiro para custo no carregamento dos estoques e o tratamento dado aos custos tipo take-or-pay. São sugeridas adaptações do modelo para utilização em quaisquer segmentos de indústria. O modelo foi aplicado com sucesso em um caso real de uma indústria do segmento químico. / The location of factories, suppliers and distribution centers has always been a problem of great complexity, mainly for companies with global operations. In the literature, there are a few models developed for facilities location in a global scale. This work proposes a Mixed Integer Linear Programming model that solves the problem minimizing the total logistic cost (fixed, transfer and distribution costs, non recoverable duties, carrying, take-or-pay, raw material, added value and handling costs) taking into consideration several echelons in the supply chain network. The main contributions of the proposed model are the considerations regarding fiscal benefits in international trade such as drawback, the pioneer carrying cost calculation and the treatment given to the take-or-pay costs. Some adaptations of the model have been suggested for use in any type of industry. The model was successfully applied in a real case of a chemical industry.

<p>U disertaciji je predstavljen pristup zasnovan na algoritmu mešovitog celobrojnog linearnog programiranja (MILP) za određivanje optimalnog broja, tipa i lokacije uređaja za automatizaciju distributivne mreže. Ugradnja različitih tipova nove opreme (daljinski kontrolisani reklozeri, sekcioneri i indikatori prolaska struje kvara) kao i relokacija postojeće opreme su istovremeno razmatrani. Prilikom određivanja optimalnog scenarija za automatizaciju, predloženi pristup uvažava troškove ispada potrošača/proizvođača usled trenutnih, kratkotrajnih i dugotrajnih ispada, najčešće korišćene pokazatelje pouzdanosti (SAIFI, SAIDI, MAIFI, i ASIDI) kao i troškove distributivnog preduzeća, asocirane uređajima za automatizaciju i ekipama koje su uključene u proces rešavanja prekida napajanja.<br />Dakle, osnovni cilj ove disertacije je, da se napravi model zasnovan na mešovitom celobrojnom linearnom programiranju koji će omogućiti određivanje najboljeg scenarija za automatizaciju distributivne mreže u slučajevima kada se ocena kvaliteta isporuke definiše preko pokazatelja pouzdanosti, preko troškova usled prekida napajanja ili kombinacijom ova dva pokazatelja.</p> / <p>The dissertation presents a mixed integer linear programming (MILP) based approach for determining the optimal number, type and location of automation devices to be installed in the network by considering different types of devices simultaneously (remotely controlled circuit breakers/reclosers, sectionalizing switches, remotely supervised fault passage indicators). Simultaneously, it determines the new (optimal) locations of the automation devices that already exist in the network. In determining the most effective network automation scenario, the proposed approach takes into account the outage cost of consumers/producers due to momentary, short-term, and long-term interruptions, the commonly used network reliability indices (SAIFI, SAIDI, MAIFI, and ASIDI) as well as the cost of automation devices and the cost of crews. It provides the best network automation scenario in distribution systems if the network reliability indices are used for measuring the distribution system reliability, if cost of interruptions is defined to all consumers/producers, and if both approaches (criteria) are used.</p>

<p>Energy management has become a major concern in the past two decades with the increasing energy prices, overutilization of natural resources and increased carbon emissions. According to the department of Energy the industrial sector solely consumes 22.4% of the energy produced in the country [1]. This calls for an urgent need for the industries to design and implement energy efficient practices by analyzing the energy consumption, electricity data and making use of energy efficient equipment. Although, utility companies are providing incentives to consumer participating in Demand Response programs, there isn’t an active implementation of energy management principles from the consumer’s side. Technological advancements in controls, automation, optimization and big data can be harnessed to achieve this which in other words is referred to as “Smart Manufacturing”. In this research energy management techniques have been designed for two SEU (Significant Energy Use) equipment HVAC systems, Compressors and load shifting in manufacturing environments using control and optimization.</p> <p>The addressed energy management techniques associated with each of the SEUs are very generic in nature which make them applicable for most of the industries. Firstly, the loads or the energy consuming equipment has been categorized into flexible and non-flexible loads based on their priority level and flexibility in running schedule. For the flexible loads, an optimal load scheduler has been modelled using Mixed Integer Linear Programming (MILP) method that find carries out load shifting by using the predicted demand of the rest of the plant and scheduling the loads during the low demand periods. The cases of interruptible loads and non-interruptible have been solved to demonstrate load shifting. This essentially resulted in lowering the peak demand and hence cost savings for both “Time-of-Use” and Demand based price schemes. </p> <p>The compressor load sharing problem was next considered for optimal distribution of loads among VFD equipped compressors running in parallel to meet the demand. The model is based on MILP problem and case studies was carried out for heavy duty (>10HP) and light duty compressors (<=10HP). Using the compressor scheduler, there was about 16% energy and cost saving for the light duty compressors and 14.6% for the heavy duty compressors</p> <p>HVAC systems being one of the major energy consumer in manufacturing industries was modelled using the generic lumped parameter method. An Electroplating facility named Electro-Spec was modelled in Simulink and was validated using the real data that was collected from the facility. The Mean Absolute Error (MAE) was about 0.39 for the model which is suitable for implementing controllers for the purpose of energy management. MATLAB and Simulink were used to design and implement the state-of-the-art Model Predictive Control for the purpose of energy efficient control. The MPC was chosen due to its ability to easily handle Multi Input Multi Output Systems, system constraints and its optimal nature. The MPC resulted in a temperature response with a rise time of 10 minutes and a steady state error of less than 0.001. Also from the input response, it was observed that the MPC provided just enough input for the temperature to stay at the set point and as a result led to about 27.6% energy and cost savings. Thus this research has a potential of energy and cost savings and can be readily applied to most of the manufacturing industries that use HVAC, Compressors and machines as their primary energy consumer.</p><br>

<p>In this thesis we address the problem of integrated software pipelining for clustered VLIW architectures. The phases that are integrated and solved as one combined problem are: cluster assignment, instruction selection, scheduling, register allocation and spilling.</p><p>As a first step we describe two methods for integrated code generation of basic blocks. The first method is optimal and based on integer linear programming. The second method is a heuristic based on genetic algorithms.</p><p>We then extend the integer linear programming model to modulo scheduling. To the best of our knowledge this is the first time anybody has optimally solved the modulo scheduling problem for clustered architectures with instruction selection and cluster assignment integrated.</p><p>We also show that optimal spilling is closely related to optimal register allocation when the register files are clustered. In fact, optimal spilling is as simple as adding an additional virtual register file representing the memory and have transfer instructions to and from this register file corresponding to stores and loads.</p><p>Our algorithm for modulo scheduling iteratively considers schedules with increasing number of schedule slots. A problem with such an iterative method is that if the initiation interval is not equal to the lower bound there is no way to determine whether the found solution is optimal or not. We have proven that for a class of architectures that we call transfer free, we can set an upper bound on the schedule length. I.e., we can prove when a found modulo schedule with initiation interval larger than the lower bound is optimal.</p><p>Experiments have been conducted to show the usefulness and limitations of our optimal methods. For the basic block case we compare the optimal method to the heuristic based on genetic algorithms.<em></em></p><p><em>This work has been supported by The Swedish national graduate school in computer science (CUGS) and Vetenskapsrådet (VR).</em></p>

Malaria is a preventable and treatable blood-borne disease whose complications can be fatal. Although many interventions exist in order to reduce the impacts of malaria, the optimal method of distributing these interventions in a geographical area with limited resources must be determined. This thesis refines a model that uses an integer linear program and a compartmental model of epidemiology called an SIR model of ordinary differential equations. The objective of the model is to find an intervention strategy over multiple time steps and multiple geographic regions that minimizes the number of days people spend infected with malaria. In this paper, we refine the resolution of the model and conduct sensitivity analysis on its parameter values.

In this thesis, we discussed various possibilities of integrating scheduling decisions with information and constraints from Advanced Process Control (APC) systems in semiconductor Manufacturing. In this context, important questions were opened regarding the benefits of integrating scheduling and APC. An overview on processes, scheduling and Advanced Process Control in semiconductor manufacturing was done, where a description of semiconductor manufacturing processes is given. Two of the proposed problems that result from integrating bith systems were studied and analyzed, they are :Problem of Scheduling with Time Constraints (PTC) and Problem of Scheduling with Equipement health Factor (PEHF). PTC and PEHF have multicriteria objective functions.PTC aims at scheduling job in families on non-identical parallel machines with setup times and time constraints.Non-identical machines mean that not all miachines can (are qualified to) process all types of job families. Time constraints are inspired from APC needs, for which APC control loops must be regularly fed with information from metrology operations (inspection) within a time interval (threshold). The objective is to schedule job families on machines while minimizing the sum of completion times and the losses in machine qualifications.Moreover, PEHF was defined which is an extension of PTC where scheduling takes into account the equipement Health Factors (EHF). EHF is an indicator on the state of a machine. Scheduling is now done by considering a yield resulting from an assignment of a job to a machine and this yield is defined as a function of machine state and job state.

Many digital signal processing and real-time streaming systems are modeled using dataflow graphs, such as Synchronous Dataflow (SDF) and Cyclo-static Dataflow (CSDF) graphs that allow static analysis and optimization techniques. However, mapping of such descriptions into tightly constrained real-time implementations requires optimization of resource sharing, buffering and scheduling across a multi-dimensional latency-throughput-area objective space. This requires techniques that can find the Pareto-optimal set of implementations for the designer to choose from. In this work, we address the problem of multi-objective mapping and scheduling of SDF and CSDF graphs onto heterogeneous multi-processor platforms. Building on previous work, this thesis extends existing two-stage hybrid heuristics that combine an evolutionary algorithm with an integer linear programming (ILP) model to jointly optimize throughput, area and latency for SDF graphs. The primary contributions of this work include: (1) extension of the ILP model to support CSDFGs with additional buffer size optimizations; (2) a further optimization in the ILP-based scheduling model to achieve a runtime speedup of almost a factor of 10 compared to the existing SDFG formulation; (3) a list scheduling heuristic that replaces the ILP model in the hybrid heuristic to generate Pareto-optimal solutions at significantly decreased runtime while maintaining near-optimality of the solutions within an acceptable gap of 10% when compared to its ILP counterparts. The list scheduling heuristic presented in this work is based on existing modulo scheduling approaches for software pipelining in the compiler domain, but has been extended by introducing a new concept of mobility-based rescheduling before resorting to backtracking. It has been proved in this work that if mobility-based rescheduling is performed, the number of required backtrackings and hence overall complexity and runtime is less. / text