In this chapter an alternative heuristic algorithm is proposed that is assumed for a deterministic flow shop scheduling problem. The algorithm is addressed to an m-machine and n-job permutation flow shop scheduling problem for the objective of minimizing the make-span when idle time is allowed on machines. This chapter is composed in a way that the different scheduling approaches to solve flow shop scheduling problems are benchmarked. In order to compare the proposed algorithm against the benchmarked, selected heuristic techniques and genetic algorithm have been used. In realistic situation, the proposed algorithm can be used as it is without any modification and come out with acceptable results.
Image compression techniques find an extensive role in the field of underwater image processing. Transform based image compression algorithms efficiency is mainly depending on the decoding methods, adopted. In this work, various decoding techniques such as Embedded Zero Tree wavelet, Set Partitioning Hierarchy Tree, Spatial Orientation Tree, Wavelet Difference Reduction and Advanced Wavelet Difference Reduction on an underwater image and the performance is measured by compression ratio, PSNR. Results clearly indicate that Zero Tree Wavelet coding performed well.
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