Mushroom Reproduction Optimization (MRO): A Novel Nature-Inspired Evolutionary Algorithm | IEEE Conference Publication | IEEE Xplore

Mushroom Reproduction Optimization (MRO): A Novel Nature-Inspired Evolutionary Algorithm


Abstract:

We introduce a new nature-inspired optimization algorithm namely Mushroom Reproduction Optimization (MRO) inspired and motivated by the reproduction and growth mechanisms...Show More

Abstract:

We introduce a new nature-inspired optimization algorithm namely Mushroom Reproduction Optimization (MRO) inspired and motivated by the reproduction and growth mechanisms of mushrooms in nature. MRO follows the process of discovering rich areas (containing goabod living conditions) by spores to grow and develop their own colonies. We thoroughly assess MRO performance based on numerous unimodal and multimodal benchmark functions as well as engineering problem instances. Moreover, to further investigate on the performance of the proposed MRO algorithm, we conduct a useful statistical evaluation and comparison with well known meta-heuristic algorithms. The experimental results confirm the high performance of MRO in dealing with complex optimization problems by discovering solutions with better quality.
Date of Conference: 08-13 July 2018
Date Added to IEEE Xplore: 04 October 2018
ISBN Information:
Conference Location: Rio de Janeiro, Brazil

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