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Welcome to INFO. INFO is an Efficient, High-performance Optimization Framework with Metaphor-free Language for Building a Better Future for Optimization Community

INFO: An Efficient Optimization Algorithm based on
Weighted Mean of Vectors

Powerful for developers. Fast for everyone. Strong for global adoption

INFO is a metaphor-free decentralized optimization method built to enable scalable, powerful, user-friendly methods for the artificial inteligence community.

Improving the performance and model


INFO Unique Features


No metaphor





INFO is a teamwork of leading names in optimization and machine learning  with over 50000 citations

"INFO: An Efficient Optimization Algorithm based on Weighted Mean of Vectors," 
Expert Systems with Applications, 2022, 116516,


Iman Ahmadianfar
Citations: 740
H-index: 18


Ali Asghar Heidari
Citations: 8265
H-index: 52

Huiling Chen
Citations: 13642
H-index: 66

Amir H Gandomi
Citations: 25774
H-index: 61

Download options for INFO
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This study presents the analysis and principle of an innovative optimizer named weighted meaN oF vectOrs (INFO) to optimize different problems. INFO is a modified weight mean method, whereby the weighted mean idea is employed for a solid structure and updating the vectors’ position using three core procedures: updating rule, vector combining, and a local search. The updating rule stage is based on a mean-based law and convergence acceleration to generate new vectors. The vector combining stage creates a combination of obtained vectors with the updating rule to achieve a promising solution. The updating rule and vector combining steps were improved in INFO to increase the exploration and exploitation capacities. Moreover, the local search stage helps this algorithm escape low-accuracy solutions and improve exploitation and convergence. The performance of INFO was evaluated in 48 mathematical test functions and five constrained engineering test cases. According to the literature, the results demonstrate that INFO outperforms other basic and advanced methods in terms of exploration and exploitation. In the case of engineering problems, the results indicate that the INFO can converge to 0.99% of the global optimum solution. Hence, the INFO algorithm is a promising tool for optimal designs in optimization problems, which stems from the considerable efficiency of this algorithm for optimizing constrained cases. The source codes of this algorithm will be publicly available at

- Download Matlab codes of weIghted meaN oF vectOrs (INFO)
- weIghted meaN oF vectOrs (INFO) is now available in github
- weIghted meaN oF vectOrs (INFO) is now available in mathworks
-- Download brief INFO section and word file


INFO is an easy and simple optimizer with secure basis and no metaphor that can be used for any class of problems. You just use the codes in your software, add your objective function, and test it.

- The proposed mean rule combines the weighted mean of two sets of vectors
(a set of random vectors and another with local best, better, and worst vectors)
as a strategy to promote exploration ability
- The proposed updating rule operator updates vectors' position using the mean
rule and convergence acceleration (CA) part, which guarantees the search
ability and convergence speed of INFO.
- The scaling rate parameter can balance the exploration and exploitation
search ability.
- To calculate the weighted mean of vectors, a wavelet function is considered to
obtain vectors' weight, which allows the algorithm to search the solution space
- The proposed vector combining operator combines global exploration and
local exploitation phases to promote the search ability and escape from local
- To ensure avoidance of locally optimal solutions, the proposed local search
operator is included.
- The convergence speed of INFO is very promising because the positions of
vectors always tend to move toward the regions with better solutions.

The PDF files of the INFO paper is available for download

The paper is online in elsevier in this link

"Based on my vision in 2022, the swarm inteligence optimization field highly suffers from wrong way of the scam metaphor-based "pseudo-novel" or "fancy" optimization algorithms. Most of these cliche methods mimic animals' searching trends and possess a small contribution to the optimization process itself. Most of these cliche methods suffer from the locally efficient performance, biased verification methods on easy problems, and high similarity between their components' interactions and unoriginal models. Most of them are a variant of another metaphor-based optimizer in mathematical terms and metaphor is to hide the action. The INFO is the second well designed method, after RUN algorithm, which attempts to go beyond the traps of metaphors and introduce a novel metaphor-free population-based optimization based on the idea of Weighted Mean of Vectors."

Ali Asghar Heidari


INFO is a tribute to Maryam Mirzakhani

Algebra's Daughter

Maryam Mirzakhani, (born May 3, 1977, Tehrān, Iran—died July 14, 2017, Palo Alto, California, U.S.), Iranian mathematician who became (2014) the first and to-date only female winner of the Fields Medal since its inception in 1936, died Friday, July 14, after a long battle with cancer. Mirzakhani was 40 years old.


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INFO: An Efficient Optimization Algorithm based on Weighted Mean of Vectors

Expert Systems with Applications, 116516, 2022

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