The optimization of a natural gas transportation network (NGTN) is typically a multiobjective optimization problem, involving for instance energy consumption minimization at the compressor stations and gas delivery maximization. However, very few works concerning multiobjective optimization of gas pipelines networks are reported in the literature. Thereby, this book aims at providing a general framework of formulation and resolution of multiobjective optimization problems related to NGTN. Firstly, the NGTN model is described. Then, various multiobjective optimization techniques belonging to two main classes, scalarization and evolutionary, commonly used for engineering purposes, are presented. The non dominated solutions are displayed in the form of a Pareto front. Finally, in the multiobjective cases, generic Multiple Choice Decision Making tools are implemented to identify the best solution among the ones displayed of the Pareto fronts.
In this book we attempt to apply swarm intelligence with numerical optimization techniques to solve multiobjective engineering problems. So, a hybrid algorithm that combines both of the trust region algorithm (numerical optimization technique) and particle swarm optimization (swarm intelligence method) to solve multiobjective optimization problems is presented. In addition, the new algorithm implemented to solve multiobjective engineering component design problems and the environmental economic dispatch problem to demonstrate the superiority of our approach and confirms its potential to solve engineering applications.
Transportation of oil and gas by the Sea characterizes challenges from a safety viewpoint. In this type of transportation, different sizes of special tankers carrying oil and gas. The marine transportation of these scarce natural riches is involved with risks and hazards, which may lead to many losses; for instance, wasting oil and gas, injuries of people, damaging ships and properties, and damaging environment. The main purpose of this thesis is to evaluate the risks, hazards, and accidents during transportation of oil and gas (mainly Crude Oil, liquefied petroleum gas, and Liquefied natural gas) by the Sea with concentrating on transport safety. Hence, a better understanding of these risks and hazards can contribute to decrease of addressed losses.
Swarm intelligence is the collective behavior of self-organized agents. In this book, a computational paradigm is proposed that adopts the particle swarm optimization within a cultural framework. The cultural algorithm adopted here consists of two space, population space and belief space including five knowledge sections: situational knowledge, normative knowledge, topographical knowledge, history knowledge, and domain knowledge. Several innovative paradigms are proposed that use the proposed cultural swarm for single objective optimization, constrained optimization, multiobjective optimization, and dynamic optimization.
Various intelligent techniques were used to solve the Shortest Path Problems in the Networks like Artificial Neural Networks (ANN), Genetic Algorithms (GA), Particle Swarm Optimization (PSO), etc. With the recent up-gradation in wireless technology,mobile communication between various nodes has become possible. One of the most important characteristics in mobile wireless networks is the topology dynamics,the network topology keeps on changing due to energy conservation or node mobility. Therefore, the shortest path routing problem becomes a Dynamic Optimization Problem (DOP) in Mobile Networks. Here the use of various optimization algorithms to solve the dynamic shortest path problem in Mobile Networks and their comparisons are discussed.
In this book Sweetening of natural gas is discussed with the help of literature survey and calculations. Different processes, commonly used in industries are compared. Different methods for calculation water contents in Natural Gas are also given in this book. A brief method for designing absorber with stage to stage calculation is also given. Optimization for sweetening process is discussed in detail. Process designers and Chemical engineers will find this book a valuable guide to gas sweetening, both in terms of its application to efficient and cost effective operations. It will prove particularly useful to readers who want a "quick reference" guide to natural gas sweetening operations and procedures as well as those readers who wish to increase their knowledge of best practices.
Many real-world problems involve two types of problem difficulty: I) multiple, conflicting objectives and II) a highly complex search space. On the one hand, instead of a single optimal solution competing goals give rise to a set of compromise solutions, generally denoted as Pareto-optimal. In the absence of preference information, none of the corresponding trade-offs can be said to be better than the others. On the other hand, the search space can be too large and too complex to be solved by exact methods. Thus, efficient optimization strategies are required that are able to deal with both difficulties. Evolutionary algorithms possess several characteristics that are desirable for this kind of problem and make them preferable to classical optimization methods. In fact, various evolutionary approaches to multiobjective optimization have been proposed since 1985, capable of searching for multiple Pareto optimal solutions concurrently in a single simulation run. The subject of this work is the improvement of multiobjective evolutionary algorithms and their application to engineering problems.
A Simple Way to Improve Design and Measure Variables in Gas Pipeline Networks: - The applications of the knowledge gained from this book’s methods and case studies can help accurate pressure, flow rate and other variable determinations in and across every point in the Gas network. This work can enable small and medium size Gas businesses to develop simple in-house methods of accurately measuring the variables in their pipeline networks. Accurately Predicting, Measuring and Determining the Pressures and Flow Rates in Pipeline networks is key ingredient to successful operations and sustainability. Pipelines are one of the most important aspects of the Oil and Gas industry. This book has shown that any gas pipeline network can be simplified and the variables of such a network can be determined with relative ease.
For the control and mitigation of hydrate formation in natural gas pipelines, multi approach study is required. Multi approach scheme of controlling parameters to avoid the hydrate formation or combination of different methods, like dehydration, inhibition, temperature and pressure control is required for controlling or removing the hydrates depending upon the specific conditions of the system. this book includes a deep study of the hydrate chemistry, hydrate detection methods and strategies to overcome the hydrate formation. This book will provide a thorough study of Hydrate formation to readers.
Transportation problem is one of the important areas in operation research, which is widely used to make a decision in engineering, business, management and many other fields. In the field of operation research, Network Analysis plays an important role to optimization. In this thesis “A study of Transportation Problem (TP) & Network Analysis with TORA applications”, we consider the transportation problem which is a linear programming problem having particular significance in optimization theory. We study some new initial and optimal solution method with some established methods and we comparing the solution. We also study some network problem to optimize the result. Finally software TORA has been used to show the variations in the methods of solving Transportation Problem (TP) & Network Problem. By using TORA, the solution can be found in short time.
In this book, we present graph theoretical analysis of two air transportation networks, Airport Network of India and World Airport Network. The heterogeneity in connectivity and long-range couplings observed in these networks suggest that certain nodes may play an important role in maintaining the stability and efficient flow through the network. Identifying and analyzing the impact of targeted removal of such “critical” nodes on the network is the major focus of this work. In this study we show the importance of network theory in applications such as improving air connectivity to promote tourism, identifying crucial airports and routes to regulate traffic in case of emergencies such as accidental failure of an airport, identifying routes for diverting traffic to avoid congestion/delay during unexpected climatic changes, and in containing the spread of disease through the air transport network. To better understand the evolution of these transportation networks, we also attempt to model the growth of air transportation networks in this study.
Revision with unchanged content. During the last few decades, multiobjective programming has received much attention for its numerous theoretical advances and successes in modeling and solving real-life decision problems in business and engineering. In extension of the classic but static concept of Pareto optimality, this book presents the more flexible notion of domination leading to novel optimization methods and enhanced decision making. After some preliminaries and review of the relevant literature, several new findings are presented that characterize nondominated sets in general vector optimization which are defined in terms of cones. Based on these results, an interactive decomposition-coordination framework is developed for the effective solution of multi-scenario or large-scale multiobjective programs arising in portfolio optimization and engineering design. The text will introduce researchers and practitioners alike to a current topic of high relevance in multiobjective programming and decision making. For his original dissertation, the author won the First Prize Outstanding Graduate Research Awards by both the College of Engineering and Science and the Graduate School of Clemson University in April 2007.
Gas-solid spouted beds are either cylindrical bed with cone base or the whole bed is in a cone shape where the gas enters as a jet. The gas forms a spout region that carries the solids upward in a diluted phase, which forms a fountain at the top of the bed where the solids fall down and move downward in the annular region. These beds have found wide and efficient applications as reactors, dryers, coaters, etc. Various design and operating variables affect the performance of these beds. Optimization helps guiding the experimental work, scale-up process, reducing the risk and cost of the design and operation. It also helps the defining of the best range of operating conditions, which can improve the performance and stability of the spouted bed reactor. The stochastic genetic algorithm technique has found more suitable search for non-linear spouted system. The results of the optimization technique compared with the experimental data using sophisticated optical probes and high accuracy pressure transducers. Advanced techniques as; Computed Tomography and Computational Fluid Dynamic were used to confirm the experimental results.
Nowadays, with the high oil price and the supply amount of oil will become less and less, the LNG (Liquefied Natural Gas) could be act as the other options to fulfill the energy demand in the world. With the rapid development of science technology and the national economy, the increase of the domestic natural gas production and the establishment of more gas pipelines; China and India will become a big player for Liquefied Natural Gas (LNG) in the world. The natural gas will become the major fuel in the town gas market.