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In this study an efficient meta-heuristic is proposed for layout optimization of truss structures by combining cellular automata (CA) and firefly algorithm (FA). In the proposed meta-heuristic, called here as cellular automata firefly algorithm (CAFA), a new equation is presented for position updating of fireflies based on the concept of CA. Two benchmark examples of truss structures are presented to illustrate the efficiency of the proposed algorithm. Numerical results reveal that the proposed algorithm is a powerful optimization technique with improved convergence rate in comparison with other existing algorithms.

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Parallel Cellular Automata (PCA) previously has been employed for optimizing bi-objective reservoir operation, where one release is used to meet both objectives. However, if a single release can only be used for one objective, meaning two separate sets of releases are needed, the method is not applicable anymore. In this paper, Multi-Step Parallel Cellular Automata (MSPCA) has been developed for bi-objective optimization of single-reservoir systems’ operation. To this end, a novel cellular automata formulation is proposed for such problems so that PCA’s incapability when dealing with them will be overcome. In order to determine all releases throughout the operation period, in each iteration – unlike PCA – two updates take place so as to calculate releases individually. Since a bi-objective problem in Dez reservoir (in southern Iran) has been solved by PCA in earlier works, the same data is used here. The results are given for a 60-months operation period, and to evaluate this method, the results of Non-Dominated Sorting Genetic Algorithm (NSGAII) is also given for the same problem. The comparison shows MSPCA, beside remarkable reduction in computational costs, gives up solutions with higher quality as well.