The alloy GaInAsN has great potential as a lower-band-gap material lattice matched to GaAs, but there is little understanding of what causes its poor optoelectronic properties and why these improve with annealing. This study provides information about the structural changes that occur when GaInAsN is annealed. The Fourier transform infrared spectra exhibit two primary features: a triplet at ∼470 cm−1 (Ga–N stretch) and two or three bands at ∼3100 cm−1 (N–H stretch). The change in the Ga–N stretch absorption can be explained if the nitrogen environment is converted from NGa4 to NInGa3 after annealing. The N–H stretch is also changed after annealing, implying a second, and unrelated, structural change.

We describe a general approach to optimization which we term `Squeaky Wheel' Optimization (SWO). In SWO, a greedy algorithm is used to construct a solution which is then analyzed to find the trouble spots, i.e., those elements, that, if improved, are likely to improve the objective function score. The results of the analysis are used to generate new priorities that determine the order in which the greedy algorithm constructs the next solution. This Construct/Analyze/Prioritize cycle continues until some limit is reached, or an acceptable solution is found. SWO can be viewed as operating on two search spaces: solutions and prioritizations. Successive solutions are only indirectly related, via the re-prioritization that results from analyzing the prior solution. Similarly, successive prioritizations are generated by constructing and analyzing solutions. This `coupled search' has some interesting properties, which we discuss. We report encouraging experimental results on two domains, scheduling problems that arise in fiber-optic cable manufacturing, and graph coloring problems. The fact that these domains are very different supports our claim that SWO is a general technique for optimization

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