2017 | OriginalPaper | Chapter
Hint
Swipe to navigate through the chapters of this book
This chapter consists of two parts. In the first part, an optimization algorithm based on some principles from physics and mechanics, which is known as the charged system search (CSS) [1]. In this algorithm the governing Coulomb law from electrostatics and the Newtonian laws of mechanics. CSS is a multi-agent approach in which each agent is a charged particle (CP). CPs can affect each other based on their fitness values and their separation distances. The quantity of the resultant force is determined by using the electrostatics laws, and the quality of the movement is determined using Newtonian mechanics laws. CSS can be utilized in all optimization fields; especially it is suitable for non-smooth or non-convex domains. CSS needs neither the gradient information nor the continuity of the search space.
Please log in to get access to this content
To get access to this content you need the following product:
Advertisement
1.
go back to reference Kaveh A, Talatahari S (2010) A novel metaheuristic optimization method: charged system search. Acta Mech 213(3–4):267–286 CrossRefMATH Kaveh A, Talatahari S (2010) A novel metaheuristic optimization method: charged system search. Acta Mech 213(3–4):267–286
CrossRefMATH
2.
go back to reference Kaveh A, Talatahari S (2010) Optimal design of truss structures via the charged system search algorithm. Struct Multidiscip Optim 37(6):893–911 CrossRef Kaveh A, Talatahari S (2010) Optimal design of truss structures via the charged system search algorithm. Struct Multidiscip Optim 37(6):893–911
CrossRef
3.
go back to reference Halliday D, Resnick R, Walker J (2008) Fundamentals of physics, 8th edn. Wiley, New York MATH Halliday D, Resnick R, Walker J (2008) Fundamentals of physics, 8th edn. Wiley, New York
MATH
4.
go back to reference Kaveh A, Talatahari S (2009) Particle swarm optimizer, ant colony strategy and harmony search scheme hybridized for optimization of truss structures. Comput Struct 87(5–6):267–283 CrossRef Kaveh A, Talatahari S (2009) Particle swarm optimizer, ant colony strategy and harmony search scheme hybridized for optimization of truss structures. Comput Struct 87(5–6):267–283
CrossRef
5.
go back to reference Coello CAC (2002) Theoretical and numerical constraint-handling techniques used with evolutionary algorithms: a survey of the state of the art. Comput Meth Appl Mech Eng 191(11–12):1CA.245–287 MathSciNetCrossRefMATH Coello CAC (2002) Theoretical and numerical constraint-handling techniques used with evolutionary algorithms: a survey of the state of the art. Comput Meth Appl Mech Eng 191(11–12):1CA.245–287
MathSciNetCrossRefMATH
6.
go back to reference Kaveh A, Talatahari S (2009) A particle swarm ant colony optimization for truss structures with discrete variable. J Constr Steel Res 65(8–9):1558–1568 CrossRef Kaveh A, Talatahari S (2009) A particle swarm ant colony optimization for truss structures with discrete variable. J Constr Steel Res 65(8–9):1558–1568
CrossRef
7.
go back to reference Tsoulos IG (2008) Modifications of real code genetic algorithm for global optimization. Appl Math Comput 203:598–607 MathSciNetMATH Tsoulos IG (2008) Modifications of real code genetic algorithm for global optimization. Appl Math Comput 203:598–607
MathSciNetMATH
8.
go back to reference Lee KS, Geem ZW (2004) A new structural optimization method based on the harmony search algorithm. Comput Struct 82:781–798 CrossRef Lee KS, Geem ZW (2004) A new structural optimization method based on the harmony search algorithm. Comput Struct 82:781–798
CrossRef
9.
go back to reference American Institute of Steel Construction (AISC) (1989) Manual of steel construction—allowable stress design, 9th edn. AISC, Chicago, IL American Institute of Steel Construction (AISC) (1989) Manual of steel construction—allowable stress design, 9th edn. AISC, Chicago, IL
10.
go back to reference Saka MP, Hasançebi O (2009) Design code optimization of steel structures using adaptive harmony search algorithm, Chapter 3. In Geem ZW (ed) Harmony search algorithms for structural design. Springer, Berlin. SCI 239:79–120 Saka MP, Hasançebi O (2009) Design code optimization of steel structures using adaptive harmony search algorithm, Chapter 3. In Geem ZW (ed) Harmony search algorithms for structural design. Springer, Berlin. SCI 239:79–120
11.
go back to reference ASCE 7–05. Minimum design loads for building and other structures. Standards ASCE/SEI 7–05 ASCE 7–05. Minimum design loads for building and other structures. Standards ASCE/SEI 7–05
12.
go back to reference Kaveh A, Talatahari S (2009) Size optimization of space trusses using Big Bang–Big Crunch algorithm. Comput Struct 87:1129–1140 CrossRef Kaveh A, Talatahari S (2009) Size optimization of space trusses using Big Bang–Big Crunch algorithm. Comput Struct 87:1129–1140
CrossRef
13.
go back to reference Kaveh A, Farahmand Azar B, Talatahari S (2008) Ant colony optimization for design of space trusses. Int J Space Struct 23(3):167–181 CrossRef Kaveh A, Farahmand Azar B, Talatahari S (2008) Ant colony optimization for design of space trusses. Int J Space Struct 23(3):167–181
CrossRef
14.
go back to reference Rajeev S, Krishnamoorthy CS (1992) Discrete optimization of structures using genetic algorithms. J Struct Eng ASCE 118(5):1233–1250 CrossRef Rajeev S, Krishnamoorthy CS (1992) Discrete optimization of structures using genetic algorithms. J Struct Eng ASCE 118(5):1233–1250
CrossRef
15.
go back to reference Schutte JJ, Groenwold AA (2003) Sizing design of truss structures using particle swarms. Struct Multidiscip Optim 25:261–269 CrossRef Schutte JJ, Groenwold AA (2003) Sizing design of truss structures using particle swarms. Struct Multidiscip Optim 25:261–269
CrossRef
- Title
- Charged System Search Algorithm
- DOI
- https://doi.org/10.1007/978-3-319-46173-1_3
- Author:
-
A. Kaveh
- Publisher
- Springer International Publishing
- Sequence number
- 3
- Chapter number
- Chapter 3