Optimization
Optimization is the process of finding the best possible solution for a given problem. This is simple when there is only one variable that needs to be optimized. For example, if one would like to find the shortest route to work, then one needs to focus on
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Abstract Optimization is the process of finding the best possible solution for a given problem. This is simple when there is only one variable that needs to be optimized. For example, if one would like to find the shortest route to work, then one needs to focus only on driving distance. However, the problem gets more complicated when there is more than one variable that needs to be considered, such as the shortest route along with minimum driving time and fuel cost. There one has to make some compromise between these multiple objectives to come up with an optimal solution. This chapter outlines the challenges of optimizing a system with multiple goals and various constraints. It discusses some of the methods, such as model-based control, hill climbing techniques, and kaizen (optimization in small steps). The chapter includes a number of examples, such as optimizing work force requirements for a project, reducing energy consumption in a home, and an objective decision-making process. Finally, there is a discussion on the various opportunities and challenges for optimization.
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What Is Optimization?
Optimization comes from the word optimum, which is defined as “the best or the most favorable condition or situation.” Thus, to optimize a system means making it to operate in a way that produces the most desirable results. In economics and social sciences, “to optimize,” means choosing the best option from a set of possible alternatives.
© Springer International Publishing Switzerland 2017 A. Ghosh, Dynamic Systems for Everyone, DOI 10.1007/978-3-319-43943-3_6
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Dynamic Systems for Everyone
For engineered systems, optimization means maintaining a set of conditions to achieve the most advantageous operation of a system. For example, there are a number of ways to operate an electric power plant, where one has to decide what constitutes its optimal performance. Those include maximum thermal efficiency, lowest possible emission, lowest possible cost, and maximum system availability. These goals are interrelated but in some cases, they are at odds with each other. For example, high excess air will result in better carbon burnout leading to less smoke and carbon monoxide production, but that will also result in lower thermal efficiency and higher emissions of harmful nitrogen oxides. These interactions need to be taken into account when trying to optimize such a system. The task of optimization is simple when there is only one variable that needs to be controlled. This is a setpoint control problem, as was the case for controlling the thickness of steel plates in a rolling mill in Chap. 1. There, the thickness of rolled steel plate is the only variable that needs to be controlled even though there are a number of factors, such as temperature of the heated steel slab, clearance between each pair of rollers, and the speed differences between pairs of rollers that affect the outcome. However, optimization of two or more interacting variables in a system can be quite complicated. For example, I may minimize travel
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