Multi-objective Flower Algorithm for Optimization

Abstract

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 the Pareto fronts for a set of test functions. We then solve a bi-objective disc brake design problem, which indeed converges quickly.

2 figures. arXiv admin note: substantial text overlap with arXiv:1312.5673

References in corpus (2)

• Bat Algorithm: A Novel Approach for Global Engineering Optimization
• Levy Flights, Non-local Search and Simulated Annealing

Cited by in corpus (4)

• Flower Pollination Algorithm: A Novel Approach for Multiobjective Optimization
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