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Flower pollination algorithm is a new nature-inspired algorithm, based on the characteristics of flowering plants. In this paper, we extend this flower algorithm to solve multi-objective optimization problems in engineering. By using the weighted sum method with random weights, we show that the proposed multi-objective flower algorithm can accurately find(More)
Multiobjective design optimization problems require multiobjective optimization techniques to solve, and it is often very challenging to obtain high-quality Pareto fronts accurately. In this paper, the recently developed flower pollination algorithm (FPA) is extended to solve multiob-jective optimization problems. The proposed method is used to solve a set(More)
Nature-inspired algorithms usually use some form of attraction and diffusion as a mechanism for exploitation and exploration. In this paper, we investigate the role of attraction and diffusion in algorithms and their ways in controlling the behavior and performance of nature-inspired algorithms. We highlight different ways of the implementations of(More)
Bat algorithm (BA) is a new stochastic optimization technique for global optimization. In the paper, we introduce both simulated annealing and Gaussian perturbations into the standard bat algorithm so as to enhance its search performance. As a result, we propose a simulated annealing Gaussian bat algorithm (SAGBA) for global optimization. Our proposed(More)