AbstractsComputer Science

Designing steel structures optimally is quite an important task for newlinestructural designers in today s world with diminishing resources besides newlineensuring the conformance of design constraints specified by design codes newlineunder applied loads Traditional approaches for the solution of optimization newlineproblem by mathematical models viz linear non linear and dynamic newlineprogramming suffered the problems of complex derivatives sensitivity to newlineinitial values and the requirement of large amount of enumeration memory newlineThese limitations have urged the researchers to rely on meta heuristic newlinealgorithms based on simulations newlineMeta heuristic algorithms imitate natural phenomena physical newlineannealing in simulated annealing human memory in a tabu search and newlineevolution in evolutionary algorithms All the currently available metaheuristic newlineoptimization algorithms require a set of algorithmic parameters to be newlinetuned to yield optimal performance The number of parameters has a major newlineimpact on the practical applicability of optimization algorithms A good newlinealgorithm would consist of a small number of problem specific parameters newlineHence the primary objective of this research is to make an attempt to develop newlinea new meta heuristic optimization algorithm African Wild Dog Algorithm newline AWDA inspired by the communal hunting behaviour of African wild dogs newlineto solve various optimization problems with minimum number of parameters newline newline%%%appendix p161-164, reference p165-177.