ME2: A Scalable Modular Meta-heuristic for Multi-modal Multi-dimension Optimization

Mohiul Islam, Nawwaf Kharma, Vaibhav Sultan, Xiaojing Yang, Mohamed Mohamed, Kalpesh Sultan

2019

Abstract

Map, Explore & Exploit (ME2) is a scalable meta-heuristic for problems in the field of multi-modal, multi-dimension optimization. It has a modular design with three phases, as reflected by its name. Its first phase (Map) generates a set of samples that is mostly uniformly distributed over the search space. The second phase (Explore) explores the neighbourhood of each sample point using an evolutionary strategy, to find a good - not necessarily optimal - set of neighbours. The third phase (Exploit) optimizes the results of the second phase. This final phase applies a simple gradient descent algorithm to find the local optima for each and all of the neighbourhoods, with the objective of finding a/the global optima of the whole space. The performance of ME2 is compared, on a fair basis, with the performance of benchmark optimization algorithms: Genetic Algorithms, Particle Swarm Optimization, Simulated Annealing and Covariance Matrix Adaptation Evolution Strategy. In most test cases it finds the global optima earlier than the other algorithms. It also scales-up, without loss of performance, to higher dimensions. Due to the distributed nature of ME2’s second and third phase, it can be comprehensively parallelized. The search & optimization process during these two phases can be applied to each sample point independently of all the others. A multi-threaded version of ME2 was written and compared to its single-threaded version, resulting in a near-linear speed-up as a function of the number of cores employed.

Paper Citation

in Harvard Style

Islam M., Kharma N., Sultan V., Yang X., Mohamed M. and Sultan K. (2019). ME2: A Scalable Modular Meta-heuristic for Multi-modal Multi-dimension Optimization. In Proceedings of the 11th International Joint Conference on Computational Intelligence (IJCCI 2019) - Volume 1: ECTA; ISBN 978-989-758-384-1, SciTePress, pages 196-204. DOI: 10.5220/0008169001960204

in Bibtex Style

@conference{ecta19,
author={Mohiul Islam and Nawwaf Kharma and Vaibhav Sultan and Xiaojing Yang and Mohamed Mohamed and Kalpesh Sultan},
title={ME2: A Scalable Modular Meta-heuristic for Multi-modal Multi-dimension Optimization},
booktitle={Proceedings of the 11th International Joint Conference on Computational Intelligence (IJCCI 2019) - Volume 1: ECTA},
year={2019},
pages={196-204},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0008169001960204},
isbn={978-989-758-384-1},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 11th International Joint Conference on Computational Intelligence (IJCCI 2019) - Volume 1: ECTA
TI - ME2: A Scalable Modular Meta-heuristic for Multi-modal Multi-dimension Optimization
SN - 978-989-758-384-1
AU - Islam M.
AU - Kharma N.
AU - Sultan V.
AU - Yang X.
AU - Mohamed M.
AU - Sultan K.
PY - 2019
SP - 196
EP - 204
DO - 10.5220/0008169001960204
PB - SciTePress