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What Is the Orthogonal Descent Optimizer?
- By Mark Nicholson
- Published 7 May 2007
- Optimization
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Rating:
Considerations for Use
The Orthogonal Descent optimizer is a new technique for the optimization of non-sequential systems. Please bear the following in mind when using it:
1. The OD optimizer is a local optimizer, like the DLS. This means that the starting point will affect the final result.
2. You may choose between the OD and DLS local optimizers when using the Hammer or Global Search global optimizers.
3. For imaging system design, and anywhere the merit function is smooth and continuous, expect the DLS optimizer to outperform the OD. The OD optimizer is particularly suited to the kind of noisy, discontinuous merit functions found in non-sequential problems, like illumination.
4. The DLS optimizer is multi-threaded (that is, it uses multiple CPUs when available) at the variable level. As DLS uses gradients, ZEMAX can compute the derivative of each variable independly, on different CPUs.
The OD optimizer requires each variable to br evaluated sequentially, and so does not multi-thread at the variable level. Instead, as it is used with non-sequential problems, the NSTR operand (which traces rays) is multi-threaded.
5. The DLS optimizer benefits from many years of development, whereas the OD optimizer has been developed only since February 2007. As a result, expect to see further improvements in how well it works. We welcome your feedback on this, as indeed on any aspect of using ZEMAX!
1. The OD optimizer is a local optimizer, like the DLS. This means that the starting point will affect the final result.
2. You may choose between the OD and DLS local optimizers when using the Hammer or Global Search global optimizers.
3. For imaging system design, and anywhere the merit function is smooth and continuous, expect the DLS optimizer to outperform the OD. The OD optimizer is particularly suited to the kind of noisy, discontinuous merit functions found in non-sequential problems, like illumination.
4. The DLS optimizer is multi-threaded (that is, it uses multiple CPUs when available) at the variable level. As DLS uses gradients, ZEMAX can compute the derivative of each variable independly, on different CPUs.
The OD optimizer requires each variable to br evaluated sequentially, and so does not multi-thread at the variable level. Instead, as it is used with non-sequential problems, the NSTR operand (which traces rays) is multi-threaded.
5. The DLS optimizer benefits from many years of development, whereas the OD optimizer has been developed only since February 2007. As a result, expect to see further improvements in how well it works. We welcome your feedback on this, as indeed on any aspect of using ZEMAX!
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1 Response to "What Is the Orthogonal Descent Optimizer?" 
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said this on 12 May 2007 3:54:27 AM PDT
It's great!!! Finally in Zemax appeared a more efficient algorithm for optimizing Non-sequental system.
Good Luck!
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