Multiobjective Optimization by a Modified Artificial Immune System Algorithm

Freschi, Fabio; Repetto, Maurizio

doi:10.1007/11536444_19

Cited by 49 publications

(19 citation statements)

References 23 publications

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“…A comprehensive experimental study has been carried out in (Chen, 2009) to compare PAIA2 with other state-of-the-art MOP algorithms, such as NSGAII (Deb, 2002), SPEA2 ) and VIS (Freschi and Reetto, 2005). The results confirmed that PAIA2 outperformed its counterparts in most cases in terms of the convergence and distribution measures.…”

Section: A Modified Population Adaptive Immune Algorithm (Paia2)mentioning

confidence: 82%

A new holistic systems approach to the design of heat treated alloy steels using a biologically inspired multi-objective optimisation algorithm

Mahfouf

Gaffour

2015

Engineering Applications of Artificial Intelligence

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Highlights •We model mechanical properties of heat treated alloy steel using interpretable fuzzy models.• We demonstrate how to locate the 'best' processing parameters and chemical compositions.• We demonstrate how to achieve certain mechanical properties.• We demonstrated a holistic systems approach to achieve 'right-first-time' production.• We unravel the power of multi-objective optimisation and interpretable fuzzy modelling. AbstractThe primary objective of this paper is to introduce a new holistic approach to the design of alloy steels based on a biologically inspired multi-objective immune optimisation algorithm. To this aim, a modified population adaptive based immune algorithm (PAIA2) and a multi-stage optimisation procedure are introduced, which facilitate a systematic and integrated fuzzy knowledge extraction process. The extracted (interpretable) fuzzy models are able to fully describe the mechanical properties of the investigated alloy steels. With such knowledge in hand, locating the 'best' processing parameters and the corresponding chemical compositions to achieve certain pre-defined mechanical properties of steels is possible. The research has also enabled to unravel the power of multi-objective optimisation (MOP) for automating and simplifying the design of the heat treated alloy steels and hence to achieve

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Section: A Modified Population Adaptive Immune Algorithm (Paia2)mentioning

confidence: 82%

A new holistic systems approach to the design of heat treated alloy steels using a biologically inspired multi-objective optimisation algorithm

Mahfouf

Gaffour

2015

Engineering Applications of Artificial Intelligence

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“…4 The module of testing of the different functions of the subsystem, including the methods of computational experiment.…”

Section: Realizationmentioning

confidence: 99%

The application of an artificial immune system for solving the identification problem

et al. 2017

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Abstact. Ecological prognosis sets the identification task, which is to find the capacity of pollution sources based on the available experimental data. This problem is an inverse problem, for the solution of which the method of symbolic regression is considered. The distributed artificial immune system is used as an algorithm for the problem solving. The artificial immune system (AIS) is a model that allows solving various problems of identification, its concept was borrowed from biology. The solution is sought using a distributed version of the artificial immune system, which is implemented through a network. This distributed network can operate in any heterogeneous environment, which is achieved through the use of cross-platform Python programming language. AIS demonstrates the ability to restore the original function in the problem of identification. The obtained solution for the test data is represented by the graph.

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“…As far as multiobjective optimization is concerned, MISA 40 is the first attempt to solve general multiobjective optimization problems using artificial immune systems. A vector Artificial Immune System (VAIS) 41 is proposed for solving multiobjective optimization problems based on the opt-aiNet. NNIA 42 is proposed for multiobjective optimization based on its unique selection technique, which only selects minority isolated nondominated individuals based on their crowding-distance values.…”

Section: Artificial Immune System and Inspired Optimization Algorithmsmentioning

confidence: 99%

A New Clonal Selection Immune Algorithm with Perturbation Guiding Search and Nonuniform Hypermutation

Zhao¹,

Zhao²,

Niu³

et al. 2010

IJCIS

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A new clonal selection immune algorithm with perturbation guiding search and non-uniform hypermutation (nCSIA) is proposed based on the idea of perturbed particle swarm algorithm and non-uniform mutation. The proposed algorithm proportional clones antibody based on the affinity, adaptively adjusts the searching steps of antibodies with hypermutation according to the adaptive variation rule of non-uniform mutation and chooses the promising antibody based on the affinity by clonal selection principle. In order to keep the balance of exploration/exploitation better, perturbation guiding search strategy is presented, which is actually an elitist learning mechanism and is borrowed from the perturbed particle swarm algorithm. In order to validate the effectiveness of nCSIA, comprehensive experiments and analysis are done based on fifteen unimodal or multimodal benchmark functions. Compared with standard and the recent algorithms, it indicates that the proposed algorithm is feasible, effective and has better performance in terms of convergence, accuracy and stability. More evident predominance emerges from further experimental comparisons with expanding search space and increasing dimensions.

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Multiobjective Optimization by a Modified Artificial Immune System Algorithm

Cited by 49 publications

References 23 publications

A new holistic systems approach to the design of heat treated alloy steels using a biologically inspired multi-objective optimisation algorithm

A new holistic systems approach to the design of heat treated alloy steels using a biologically inspired multi-objective optimisation algorithm

The application of an artificial immune system for solving the identification problem

A New Clonal Selection Immune Algorithm with Perturbation Guiding Search and Nonuniform Hypermutation

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