Fish shoal optimization for identification of the most suitable revetment stone for design of minimum cost earthen canals carrying sediment-laden flow. Issue 2 (4th May 2018) - Gupta, Sanjay K.; Mishra, Umank; Datta, D.; Singh, Vijay P.
Abstract: A novel variant of particle swarm optimization (PSO), referred to as Fish Shoal Optimization (FSO), is developed to add an additional capability to its ancestor PSO to handle concurrently three different types of stones for the design of minimum cost earthen canals whose side slopes are riprap riveted and bottom is unlined with the most suitable type of stone. Costs of land acquisition and freeboard provision (fixed magnitude and depth-dependent scenarios) for a non-symmetric canal carrying sediment-laden flow are accounted for. The FSO concurrently handled various types of riprap stones in a single program to portray its resemblance with the biological character of a fish shoal (aggregation of mixed species of fish in nature). It allowed interaction of dissimilar species of shoal – the social characteristic of PSO and stiff competition – a feature of Genetic Algorithms, among their own and other groups' members to yield the minimum cost design of canals having symmetric shape and angular particles as the most suitable revetment stone. The FSO yielded not only the minimum cost canals but also hydraulically efficient designs with 1.32, 4.86, 4.42, 4.28, and 4.40% less costs than those obtained by PSO for five different freeboard scenarios, respectively.