Formation of the composition of programs for the knowledge–intensive industry development using bacterial optimization algorithms and fuzzy logic methods

Today the knowledge–intensive industry development is carried out by the programs that combine a set of innovation and investment projects aimed at achieving a single goal and implemented in general constraints. The presence of a larger number of project characteristics (in particular, terms, resources, performers, etc.), which must be taken into account when forming the composition of the program, leads to the formulation of the problem of multicriteria optimization. As its solution, it is proposed to use an algorithm of bacterial optimization, supplemented by a procedure for forming initial positions using fuzzy logic methods.

Download Full-text

Fuzzy Logic Hybrid Extensions of Neural and Optimization Algorithms: Theory and Applications

10.1007/978-3-030-68776-2 ◽

2021 ◽

Keyword(s):

Fuzzy Logic ◽

Optimization Algorithms

Download Full-text

A Fuzzy Adaptive Simplex Search Optimization Algorithm

Volume 1: 25th Design Automation Conference ◽

10.1115/detc99/dac-8586 ◽

1999 ◽

Author(s):

Mohamed B. Trabia ◽

Xiao Bin Lu

Keyword(s):

Fuzzy Logic ◽

Optimization Algorithms ◽

Test Problems ◽

Objective Functions ◽

Fuzzy Logic Controllers ◽

Design Problems ◽

Simplex Search ◽

Search Optimization ◽

Engineering Design Problems ◽

Fuzzy Adaptive

Abstract Optimization algorithms usually use fixed parameters that are empirically chosen to reach the minimum for various objective functions. This paper shows how to incorporate fuzzy logic in optimization algorithms to make the search adaptive to various objective functions. This idea is applied to produce a new algorithm for minimization of a function of n variables using an adaptive form of the simplex method. The search starts by generating a simplex with n+1 vertices. The algorithm replaces the point with the highest function value by a new point. This process comprises reflecting the point with the highest function value in addition to expanding or contracting the simplex using fuzzy logic controllers whose inputs incorporate the relative weights of the function values at the simplex points. The efficiency of the algorithm is studied using a set of standard minimization test problems. This algorithm generally results in a faster convergence toward the minimum. The algorithm is also applied successfully to two engineering design problems.

Download Full-text

Design of interval type-2 fuzzy logic systems using prior knowledge via optimization algorithms

2011 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE 2011) ◽

10.1109/fuzzy.2011.6007364 ◽

2011 ◽

Author(s):

Tiechao Wang ◽

Jianqiang Yi ◽

Tiechao Wang

Keyword(s):

Fuzzy Logic ◽

Prior Knowledge ◽

Optimization Algorithms ◽

Fuzzy Logic Systems ◽

Logic Systems ◽

Interval Type

Download Full-text

Comparing Convergence of PSO and SFLA Optimization Algorithms in Tuning Parameters of Fuzzy Logic Controller

AETA 2015: Recent Advances in Electrical Engineering and Related Sciences - Lecture Notes in Electrical Engineering ◽

10.1007/978-3-319-27247-4_39 ◽

2016 ◽

pp. 457-467 ◽

Cited By ~ 1

Author(s):

Duc-Hoang Nguyen ◽

Manh-Dung Ngo

Keyword(s):

Fuzzy Logic ◽

Fuzzy Logic Controller ◽

Optimization Algorithms ◽

Tuning Parameters

Download Full-text

Assessment of Investment Attractiveness of Projects on the Basis of Environmental Factors

Sustainability ◽

10.3390/su11092544 ◽

2019 ◽

Vol 11 (9) ◽

pp. 2544 ◽

Cited By ~ 15

Author(s):

Sayabek Ziyadin ◽

Elena Streltsova ◽

Alex Borodin ◽

Nataliya Kiseleva ◽

Irina Yakovenko ◽

...

Keyword(s):

Fuzzy Logic ◽

Decision Support ◽

Environmental Factors ◽

Mathematical Models ◽

Mathematical Apparatus ◽

Investment Projects ◽

Environmental Criteria ◽

Structured Knowledge ◽

Matlab Package ◽

The Impact

This article is devoted to the creation of intelligent modelling tools for decision support in the evaluation of intellectual projects submitted for financing, as based on qualitatively defined characteristics. The economic and mathematical models that form the basis of the toolkit are constructed using the mathematical apparatus of fuzzy logic, which allows for the description of poorly structured knowledge of specialists, as well as their application in solving questions about the extent of the impact of the proposed projects on the environment. The authors classify investment projects according to the degree of impact on the environment, the environmental criteria required by the investor for the evaluation of investment projects, and the formal formulation of the problem of evaluation of investment projects when taking into account the environmental factor. The toolkit was created based on the concept of intellectualization, where economic and mathematical models for the evaluation of investment projects are programmatically implemented via the tools and functions available in the MATLAB package.

Download Full-text