Design optimization techniques

The following sections outline each of these four optimization techniques. 

Area optimization is a well-studied field in digital electronics. Early techniques addressed simple matrix-based manipulation for Boolean algebra. Later developments incorporated optimization based on dorit-care states. At the time of writing a whole host of deterministic and non-deterministic methods are available general purpose or targeted at particular structures 

Boolean logic is fairly easy to optimize, and most synthesizers perform close to optimal. Knowledge of the imderlying technology strongly afiects the optimization (e.g. whether or not four-input gates are available). State-machines are equally well optimized. 

Where area optimization is more difficult is when particular device technologies are used. For example, the XILINX FPGA operates a number of CLBs. Each CLB can compute up to five-input Boolean expressions. If the expression involves six inputs then a second CLB is needed. If four inputs are needed, then there is unlikely to be any area saving. Here the relationship between gate coimt and area is non-linear and thus substantially harder to calculate. Special-purpose optimizers may need to be used for these cases. 

Some measure of speed optimization is usually achieved through area optimization, as the area optimization removes redundant circuitry and can shorten the critical path of the circuit. However, further speed optimization can also be performed. 

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Although such numerical die design optimization techniques significantly improve the flow uniformity and reduce the level of internal stresses leading to extrudate distortion,... 

The use of nuclear power as a source of energy for potable water production is both technically viable and economically competitive. CANDESAL s system integration and design optimization techniques provide significant improvements in the efficiency of energy use and the economics of water production. These features will allow nuclear desalination to play an important role in the solution to the Rowing global demand for water and electricity. 

A study on the design of the heating configuration for an existing pultrusion die has been carried out by Awa et al. (1992). The design optimization technique was used to synthesize the heating configuration in terms of the number of heaters, the power input as well as the locations of the heaters for a laboratory-scale die to produce the required temperature profile for a pultrusion product. 

Because of the relative slowness of main memory (compared with the CPU), most computers have a much smaller, but much faster cache memory subsystem that augments main memory. The size of the cache memory and the extent to which a program can utilize the cache can be critical deterrninants of performance. Again, there are some common optimization techniques designed to maximize cache utilization. 

Dong, Z. 1997 Tolerance Synthesis by Manufacturing Cost Modeling and Design Optimization. In Zhang, H. (ed.). Advanced Tolerancing Techniques. NY Wiley Interscience. 

In addition to evolutionary search strategies such as GAs, there are a number of other search techniques that are employed for design optimization. 

As has been discussed in Chapter One, mathematical programming (or optimization) is a powerful tool for process integration. For an overview of c mization and its application in pollution prevention, the reader is referred to El-Halwagi (1995). In this chapter, it will be shown how optimization techniques enable the designer to ... 

The analytical tools to accomplish laminate design are at least twofold. First, the invariant laminate stiffness concepts developed by Tsai and Pagano [7-16 and 7-17] used to vary laminate stiffnesses. Second, structural optimization techniques as described by Schmit [7-12] can be used to provide a decision-making process for variation of iami-nate design parameters. This duo of techniques is particularly well suited to composite structures design because the simultaneous possibility and necessity to tailor the material to meet structural requirements exists to a degree not seen in isotropic materials. 

The death of old products, the birth of new ones, changing demands, and the need to compose the optimal hierarchical production plan with an optimal use of the equipment and the shortest possible total production time make the timing of production more important than plant design. The use of rigorous optimization techniques can be most profitable at production planning and scheduling of existing batch plants, especially multipurpose plants. 

Figure 4.33 Separation of nine substituted naphthalenes using the sixture-design statistical technique to optimize the composition of the mobile phase (Reproduced with permission from ref. 480. Copyright John Wiley and Sons).

Glajch, J. L., Kirkland, J. J., Squire, K. M., and Minor, J. M., Optimization of solvent strength and selectivity for reversed-phase liquid chromatography using an interactive mixture-design statistical technique, /. Chromatogr., 199, 57, 1980. 

The key to successful application of the experimental optimization techniques is based on adequate experimental design. A system based on this experimental design (see Table 4), but utilizing a special analog computer for analysis, was presented by Clax-ton [19] as the Firestone Computer/Optimizer. 

Adaptation of the modified factorial techniques to desktop computers has also been accomplished [24, 25]. Down et al. [25] presented this concept and applied the programs to a tablet problem. The statistics involved were presented in some detail. A similar design was also used to study a high-performance liquid chromatography (HPLC) analysis [26]. In an unusual application, optimization techniques were even used to study the formulation of a culture medium in the field of virology [27]. 

Optimization techniques are procedures to make something better. Some criteria must be established to determine whether something is better. The single criterion that determines the best among a number of alternatives is referred to as the performance index or the objective function. Economically, this is the expected profit for a plant design. It may be expressed as the net present value of the project. 

An extension of the linearization technique discussed above may be used as a basis for design optimization. Such an application to natural gas pipeline systems was reported by Flanigan (F4) using the so-called constrained derivatives (W4) and the method of steepest descent. We offer a more concise derivation of this method following a development by Bryson and Ho (B14). 

Publications on optimal design of tree networks are further divided into single-branch trees or pipelines (C6, F4, L3, L6, S8) and many-branch trees (B7, C7, F4, Kl, K2, M3, M9, Nl, R5, W10, Y1, Zl). For our purposes, since the pipeline problems can always be solved using the optimization methods developed for the many-branch tree networks, we need to dwell no further on this special case. On the other hand, it is important to note that the form of the objective function could influence the applicability of a given optimization method. For the sake of concreteness, problem formulations and optimization techniques will be discussed in the context of applications. 

A more subjective approach to the multiresponse optimization of conventional experimental designs was outlined by Derringer and Suich (22). This sequential generation technique weights the responses by means of desirability factors to reduce the multivariate problem to a univariate one which could then be solved by iterative optimization techniques. The use of desirability factors permits the formulator to input the range of property values considered acceptable for each response. The optimization procedure then attempts to determine an optimal point within the acceptable limits of all responses. 

Adequate resolution of the components of a mixture in the shortest possible time is nearly always a principal goal. Establishing the optimum conditions by trial and error is inefficient and relies heavily on the expertise of the analyst. The development of computer-controlled HPLC systems has enabled systematic automated optimization techniques, based on statistical experimental design and mathematical resolution functions, to be exploited. The basic choices of column (stationary phase) and detector are made first followed by an investigation of the mobile phase composition and possibly other parameters. This can be done manually but computer-controlled optimization has the advantage of releasing the analyst for other... 

Each chapter presents several detailed studies illustrating the application of various optimization techniques. The following matrix shows the classification of the examples with respect to specific techniques. Truly optimal design of process plants cannot be performed by considering each unit operation separately. Hence, in Chapter 15 we discuss the optimization of large-scale plants, including those represented by flowsheet simulators. 

This chapter contains examples of optimization techniques applied to the design and operation of two of the most common staged and continuous processes, namely, distillation and extraction. We also illustrate the use of parameter estimation for fitting a function to thermodynamic data. 

Presentation of each optimization technique is followed by examples to illustrate an application. We also have included many practically oriented homework problems. In university courses, this book could be used at the upper-division or the first-year graduate levels, either in a course focused on optimization or on process design. The book contains more than enough material for a 15-week course on optimization. Because of its emphasis on applications and short case studies in Chapters 11-16, it may also serve as one of the supplementary texts in a senior unit operations or design course. 

Ahlfeld, D. P. and Sawyer, C. S., 1990, Well Location in Capture Zone Design Using Simulation and Optimization Techniques Ground Water, Vol. 28, No. 4, pp. 507-512. 

I hope that this chapter provides a fitting introduction to the complex task of active pharmaceutical ingredient product design through ciystallization, and most importantly that it will stimulate work and encourage further growth in the application of thermodynamic models and optimization techniques in this area. 

V.M. Ashley P. Linke, 2004, A novel approach for reactor network network synthesis using knowledge discovery and optimization techniques, Chemical Engineering Research Design, 82 (A8) 952-960... 

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