Heuristic optimization

There are two widely used heuristics for optimum distillation design. We will discuss both of them in this section and compare the designs that result firom applying each. It should be emphasized that they cannot both be used simultaneously for rigorous design because fixing one of the two completely specifies the design of the column. 

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A true optimization of decisions based on exact or heuristic optimization algorithms... 

Tedder, D.W. and Rudd, D.F., "Parametric Studies in Industrial Distillation Part I. Design Comparison Part II. Heuristic Optimization and Part III. Design Methods and their Evaluation," AIChE J. Vol. 24, No. 2, pp 303-334, 1978. 

Wemisch L, Hery S, Wodak S (2000) Automatic protein design with aU atom force fields by exact and heuristic optimization. J Mol Biol 301 713-736... 

Tedder, D.W., and D.F. Rudd, Parametric Studies in Industrial Distillation n. Heuristic Optimization, AIChE J., 24, 316 (1978b). 

Now that the pressure has been determined and the product specifications attained, we need to go back and find the optimum feed tray. In addition, the minimum reflux ratio and the minimum number of trays can be determined. These will be useful for heuristic optimization, which is discussed in detail in Chapter 4. 

As a heuristically-optimized data collection strategy for rapid volumetric MRI data acquisition trajectories, Durga, is presented. This work demonstrates that much higher rates of under-sampling are possible with an asymmetric set of trajectories, with very little loss in resolution, but the addition of noise-like artefacts. Durga further minimizes collection time by... 

Pedersen, M.E.H. Tuning and simplifying heuristical optimization. Master s thesis. University of Southampton (2010)... 

Naess A, Gaidai O, Batsevych O (2010) Prediction of extreme response statistics of narrow-band random vibrations. J Eng Mech 136(3) 290-298 Ngatchou PN, Zarei A, Fox WLJ, El-Sharkawi MA (2008) Pareto multiobjective optimization. In Lee KY, El-Sharkawi MA (eds) Modem heuristic optimization techniques. Wiley-Interscience, Piscataway, pp 189-207... 

The optimization of the backtracking algorithm usually consists of an application of several heuristics which reduce the number of candidate atoms for mapping from Gq to Gj. These heuristics are based on local properties of the atoms such as atom types, number of bonds, bond orders, and ring membership. According to these properties the atoms in Gq and Gj are separated into different classes. This step is known in the literature as partitioning [13]. Table 6.1 illustrates the process of partitioning. 

The initial aim of the procedure is to generate a reasonable base case design that can be used for preliminary economic evaluation of the process. This can subsequently be optimized and/or compared with any process alternatives that are identified. The complete process is always considered at each decision level, but additional fine detail is added to the structure of the flowsheet at any stage. Established heuristics and equipment selection procedures are used together with new process synthesis insights to guide each flowsheet decision. 

The conventional approach to optimize a heterogeneous catalytic process is based on heuristics, and trial and error, which could take a considerable amount... 

A broad class of optimization strategies does not require derivative information. These methods have the advantage of easy implementation and little prior knowledge of the optimization problem. In particular, such methods are well suited for quick and dirty optimization studies that explore the scope of optimization for new problems, prior to investing effort for more sophisticated modeling and solution strategies. Most of these methods are derived from heuristics that naturally spawn numerous variations. As a result, a very broad literature describes these methods. Here we discuss only a few important trends in this area. 

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