Design optimisation of cost of the pressure vessel through MATLAB and simulation through ANSYS

S. Elizabeth Amudhini Stephen, D. Christu Nesam David and A. Joe Ajay

International Journal of Mathematics in Operational Research, 2019, vol. 14, issue 4, 473-494

Abstract: The objective functions used in engineering optimisation are complex in nature with many variables and constraints. Conventional optimisation tools sometimes fail to give the global optimal points. Very popular methods like genetic algorithm, pattern search, simulated annealing, and gradient search are useful methods to find global optima related to engineering problems. This paper attempts to use new non-traditional optimisation algorithms which are used to find the minimum cost of designing a pressure vessel to obtain global optimum solutions. The cost, number of iterations and the total elapsed time to complete the problems are all compared using these ten non-traditional optimisation methods. The validation is done through simulation using ANSYS.

Keywords: pattern search; simulate annealing; GODLIKE; cuckoo search; firefly algorithm; flower pollination; ant lion optimiser; gravitational search algorithm; multi-verse optimiser; simulation ANSYS. (search for similar items in EconPapers)
Date: 2019
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