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A Population Adaptive Based Immune Algorithm for Solving Multi-objective Optimization Problems [chapter]

Jun Chen, Mahdi Mahfouf
2006 Lecture Notes in Computer Science  
To this aim, a novel Population Adaptive Based Immune Algorithm (PAIA) inspired by Clonal Selection and Immune Network theories for solving multi-objective optimization problems (MOP) is proposed.  ...  The algorithm is shown to be insensitive to the initial population size; the population and clone size are adaptive with respect to the search process and the problem at hand.  ...  Fabio Freschi for his kind help in providing the results of applying VIS to the ZDT1~ZDT4 test suite.  ... 
doi:10.1007/11823940_22 fatcat:noomip7bfjaatgtk5kr45ihz5q

Advancement in the twentieth century in artificial immune systems for optimization: Review and future outlook

Eugene Y. C. Wong, Henry Y. K. Lau
2009 2009 IEEE International Conference on Systems, Man and Cybernetics  
problems, especially on multi-objective optimizations.  ...  Exploration and adoption of the inspired immune theories in clonal selection, immune network, negative selection, and danger signaling is becoming a popular basis for algorithm design for solving optimization  ...  Luh et al. (2003) proposed Multi-objective Immune Algorithm (MOIA) to search for Pareto optimal solutions in multi-objective optimization problems.  ... 
doi:10.1109/icsmc.2009.5346835 dblp:conf/smc/WongL09 fatcat:eu2xpvl2tjgc5b376cqa3hzega

A Self-adaptive Multipeak Artificial Immune Genetic Algorithm

Qingzhao Li, Fei Jiang
2016 TELKOMNIKA (Telecommunication Computing Electronics and Control)  
This paper proposes an self-adaptive multi-peak immune genetic algorithm (SMIGA) and this algorithm integrates immunity thought in the biology immune system into the evolutionary process of genetic algorithm  ...  The simulation experiment shows that the method of this paper can better solve the optimization problem of multi-peak functions, realize global optimum search, overcome the prematurity problem of the antibody  ...  The steps to solve optimization problems with immune algorithm are classified as follows.  ... 
doi:10.12928/telkomnika.v14i2.2753 fatcat:xv47qrfeenb4bhrmfdpgp6q57y

Immune Clone Algorithm to Solve the Multi-object Problems [chapter]

Liang Zhou, Jianguo Zheng
2011 Communications in Computer and Information Science  
This algorithm will treat these COPs as multi-objective optimization problems, and it is based on the concept of Pareto optimization to solve COPs.  ...  In this paper, a new improved artificial immune algorithm is proposed and then used for solving constrained optimizations problems (COPs).  ...  Yang dongdong et al proposed a new preference rank immune memory clone selection algorithm to solve the problem of multi-objective optimization with al. pointed out that the new algorithm based on the  ... 
doi:10.1007/978-3-642-18134-4_36 fatcat:tx4uaksu5jbyzdipy6gu7pqdzi

An Adaptive Multi-objective Immune Algorithm for Optimal Design of Truss Structures

Liyu Xie, Hesheng Tang, Changyuan Hu, Songtao Xue
2016 Journal of Asian Architecture and Building Engineering  
In this paper, an adaptive immune clone selection algorithm for multi-objective optimization (AICSAMO) is proposed.  ...  According to the comparison of AICSAMO with various multi-objective optimization algorithms developed recently, the simulation results illustrate that AICSAMO has remarkable performance in finding a wider  ...  is the state-of-the-art algorithm for solving multi-objective optimization problems.  ... 
doi:10.3130/jaabe.15.557 fatcat:ewo2iuvd5jdkvnaoejydqwnu4q

Special issue on "Data-driven evolutionary optimization"

Yaochu Jin, Jinliang Ding
2017 Soft Computing - A Fusion of Foundations, Methodologies and Applications  
For this reason, the second paper titled "Hyper multi-objective evolutionary algorithm for multi-objective optimization problems" by Guo et al. combines three popu-B Yaochu Jin lar multi-objective evolutionary  ...  Many real-world optimization problems do not have an analytical objective function for performing optimization.  ...  The seventh paper, "A hybrid evolutionary algorithm with adaptive multi-population strategy for multiobjective optimization problems" by Wang et al. proposes a multipopulation evolutionary algorithm that  ... 
doi:10.1007/s00500-017-2842-x fatcat:ofzrxnd6cnc2foe2zsc2nlohyi

A General Framework for Multi-Objective Optimization Immune Algorithms

Yunfang Chen
2012 International Journal of Intelligent Systems and Applications  
During the past decade more than ten kinds of Mult i-Objective optimization algorith ms based on AIS were proposed and showed outstanding abilities in solving this kind of problem.  ...  The experiment results showed the framework is very suitable to develop the various multi-objective optimization immune algorithms.  ...  for solving MOP problems.  ... 
doi:10.5815/ijisa.2012.06.01 fatcat:l57ji2b2tvhj5mc65vabtn3qaq

Constraint-Handling in Evolutionary Optimization; Efrén Mezura-Montes (Editor)

Efrén Mezura-Montes
2009 Journal of Computer Science and Technology  
The use of evolutionary and swarm intelligence algorithms, has become a very popular option to solve complex real-world optimization problems.  ...  Therefore, the design of constraint-handling mechanism is nowadays considered a research area within natureinspired computation for optimization.  ...  Yen presents in Chapter 6 a parameter-free adaptive penalty function coupled with a distance measure for constrained evolutionary multi-objective optimization.  ... 
doaj:e615e297b45f4cc984f1ad503ef96f25 fatcat:4zirkdhlabbmxe4y4dbe7zmdgq

A Hybrid Multi-objective Immune Algorithm for Numerical Optimization

Chris S. K. Leung, Henry Y. K. Lau
2016 Proceedings of the 8th International Joint Conference on Computational Intelligence  
In this paper, a hybrid multi-objective immune optimization algorithm based on the concepts of the biological evolution and the biological immune system including clonal selection and expansion, affinity  ...  Its performance is measured and compared with other wellknown multi-objective optimization algorithms.  ...  This research develops a hybrid immune algorithm -SCMIA for solving multi-objective optimization problems.  ... 
doi:10.5220/0006014201050114 dblp:conf/ijcci/LeungL16 fatcat:h7cgviq2efcrjkasaodhvxtnai

Agent-Based Multi-Objective Evolutionary Algorithms with Cultural and Immunological Mechanisms [chapter]

Leszek Siwik, Rafa Drezewski
2009 Evolutionary Computation  
Evolutionary algorithms may be also applied to multimodal and multi-objective problems (for example compare (Deb, 2001) ).  ...  Evolutionary algorithms are heuristic techniques for finding (sub)optimal solutions for hard global optimization problems.  ...  Two goals of multi-objective optimization In the consequence, despite that using only one single measure during assessing the effectiveness of (evolutionary) algorithms for multi-objective optimization  ... 
doi:10.5772/9621 fatcat:exrme2djsjatxc3d5zps4w5p6u

A multi-modal immune algorithm for the job-shop scheduling problem

Guan-Chun Luh, Chung-Huei Chueh
2009 Information Sciences  
A novel approach multi-modal immune algorithm is proposed for finding optimal solutions to job-shop scheduling problems emulating the features of a biological immune system.  ...  of adaptive immune responses.  ...  Until recently, immune algorithm emulating the entire features of biological immune system was proposed for solving multi-objective [27] and multi-modal [28] optimization problems.  ... 
doi:10.1016/j.ins.2008.11.029 fatcat:ro6b5oau6jc2xgzipr3yqnl6cm

A multi-objective approach for multi-application NoC mapping

Johanna Sepulveda, Marius Strum, Wang Jiang Chau, Guy Gogniat
2011 2011 IEEE Second Latin American Symposium on Circuits and Systems (LASCAS)  
In this paper we propose the use of a multi-objective adaptive immune algorithm (M 2 AIA), an evolutionary approach to solve the multi-application NoC mapping problem.  ...  IP mapping has been solved for single application systems.  ...  In this work we propose M 2 AIA an improved version of our Multi-objective Adaptive Immune Algorithm (MAIA), to solve the multi-application NoC mapping problem.  ... 
doi:10.1109/lascas.2011.5750275 fatcat:orfygbwqknakfkyuesh3f4csnu

Immune Optimization Approach for Dynamic Constrained Multi-Objective Multimodal Optimization Problems

Zhuhong Zhang, Min Liao, Lei Wang
2012 American Journal of Operations Research  
This work investigates one immune optimization approach for dynamic constrained multi-objective multimodal optimization in terms of biological immune inspirations and the concept of constraint dominance  ...  The first, inspired by the function of immune surveillance, is designed to detect the change of such kind of problem and to decide the type of a new environment; the second generates an initial population  ...  Dynamic Multi-Objective Immune Optimization (DMIO) Since Carlos et al. proposed a simple artificial immune system to solve static multi-objective optimization problems [13, 14] , multi-objective immune  ... 
doi:10.4236/ajor.2012.22022 fatcat:ddew7x65m5ap7itpwhflaaw7r4

Optimal Therapeutic Control Modeling for Immune System Response

Pramila Bajpai, Ashish Chaturvedi, A. P. Dwivedi
2011 International Journal of Computer Applications  
Paper demonstrates the stochastic optimal control model to enhance immune system response.  ...  Immune system response can be amplified by agents that kill the pathogen, which stimulates the production of antibodies and implies the enhancement in the health of the organ.  ...  Being a population-based approach, GA are well suited to solve multi-objective optimization problems.  ... 
doi:10.5120/2498-3376 fatcat:rha44gwjgba5lhw7opy5slf23a

Optimal Siting of Distributed Generators in a Distribution Network using Artificial Immune System

Meera P.S., S. Hemamalini
2017 International Journal of Electrical and Computer Engineering (IJECE)  
Optimal location is obtained by evaluating a global multi-objective technical index (MOTI) using a weighted sum method.  ...  Solutions obtained using AIS are compared with Genetic algorithm (GA) and Particle Swarm optimization (PSO) solutions for the same objective function.</p>  ...  Clonal Selection Based AIS Algorithm In this algorithm, initially a random population of antibodies is generated. These are the candidate solutions for the optimization problem.  ... 
doi:10.11591/ijece.v7i2.pp641-649 fatcat:tfhcfcoetjhvpgzfclcnxlmyey
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