Optimal design of engineering structures

The basic information required to utilize one of possible computation tools/algorithms (mainly the evolution strategy) to solve a wide class of real practical engineering optimization problems is presented and discussed in the present paper. The effectiveness of the considered method is demonstrated by the possibility of the use of different form of objective functions, various and numerous nonlinear constraints and different types of design variables (continuous, discrete, real, integer). The sensitivity of the algorithm to the choice of the evolution strategy parameters is also discussed herein. The generality of the evolution strategy is illustrated by the analysis of three examples dealing with: the design of helical springs, the buckling of cylindrical composite panels and the buckling of pressure vessels with domed heads.

[1]  Boon-Hee Soong,et al.  Broadcast scheduling in packet radio networks using mixed tabu-greedy algorithm , 2004 .

[2]  Fred W. Glover,et al.  Tabu Search for Nonlinear and Parametric Optimization (with Links to Genetic Algorithms) , 1994, Discret. Appl. Math..

[3]  Lipo Wang,et al.  An Ant Colony Optimization Algorithm Based on the Experience Model , 2009, 2009 Fifth International Conference on Natural Computation.

[4]  B. Nebel.  The FF Planning System : Fast Plan Generation , 2011 .

[5]  Marco Dorigo,et al.  Ant colony optimization theory: A survey , 2005, Theor. Comput. Sci..

[6]  F. Glover.  HEURISTICS FOR INTEGER PROGRAMMING USING SURROGATE CONSTRAINTS , 1977 .

[7]  Sa Li,et al.  Minimizing Interference in Mobile Communications Using Genetic Algorithms , 2002, International Conference on Computational Science.

[8]  J. McCall,et al.  Genetic algorithms for modelling and optimisation , 2005 .

[9]  Lipo Wang,et al.  A gradual noisy chaotic neural network for solving the broadcast scheduling problem in packet radio networks , 2006, IEEE Trans. Neural Networks.

[10]  Hiroshi Nozawa,et al.  A neural network model as a globally coupled map and applications based on chaos. , 1992, Chaos.

[11]  J. S. F. Barker,et al.  Simulation of Genetic Systems by Automatic Digital Computers , 1958 .

[12]  L.N. de Castro,et al.  An artificial immune network for multimodal function optimization , 2002, Proceedings of the 2002 Congress on Evolutionary Computation. CEC'02 (Cat. No.02TH8600).

[13]  Lipo Wang,et al.  A noisy chaotic neural network for solving combinatorial optimization problems: stochastic chaotic simulated annealing , 2004, IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics).

[14]  John H. Holland,et al.  Outline for a Logical Theory of Adaptive Systems , 1962, JACM.

[15]  S. Wu,et al.  GENETIC ALGORITHMS FOR NONLINEAR MIXED DISCRETE-INTEGER OPTIMIZATION PROBLEMS VIA META-GENETIC PARAMETER OPTIMIZATION , 1995 .

[16]  Wen Liu,et al.  Delay-Constrained Multicast Routing Using the Noisy Chaotic Neural Networks , 2009, IEEE Transactions on Computers.

[17]  A. Muc,et al.  Genetic algorithms and finite element analysis in optimization of composite structures , 2001 .

[18]  Manuel López-Ibáñez,et al.  Ant colony optimization , 2010, GECCO '10.

[19]  Bülent Çatay,et al.  A Tabu Search Approach for the NMR Protein Structure-Based Assignment Problem , 2012, IEEE/ACM Transactions on Computational Biology and Bioinformatics.

[20]  E. Sandgren,et al.  Nonlinear Integer and Discrete Programming in Mechanical Design Optimization , 1990 .

[21]  Pablo Moscato,et al.  Memetic algorithms: a short introduction , 1999 .

[22]  C. D. Gelatt,et al.  Optimization by Simulated Annealing , 1983, Science.

[23]  Aleksander Muc,et al.  An Evolution Strategy in Optimal Design of Composite Structures , 2004 .

[24]  Limsoon Wong,et al.  Key node selection for containing infectious disease spread using particle swarm optimization , 2009, 2009 IEEE Swarm Intelligence Symposium.

[25]  Rajeev Motwani,et al.  Randomized Algorithms , 1995, SIGA.

[26]  Richard W. Eglese,et al.  Simulated annealing: A tool for operational research , 1990 .

[27]  Herbert S. Wilf.  Algorithms and complexity (2. ed.) , 2002 .

[28]  Lipo Wang,et al.  Rule extraction by genetic algorithms based on a simplified RBF neural network , 2001, Proceedings of the 2001 Congress on Evolutionary Computation (IEEE Cat. No.01TH8546).

[29]  Lipo Wang,et al.  Genetic algorithms for optimal channel assignment in mobile communications , 2002, Proceedings of the 9th International Conference on Neural Information Processing, 2002. ICONIP '02..

[30]  David H. Wolpert,et al.  No free lunch theorems for optimization , 1997, IEEE Trans. Evol. Comput..

[31]  Lipo Wang,et al.  Ant Colony Optimization for the Traveling Salesman Problem Based on Ants with Memory , 2008, 2008 Fourth International Conference on Natural Computation.

[32]  Lipo Wang,et al.  Optimal location management in mobile computing with hybrid genetic algorithm and particle swarm optimization (GA-PSO) , 2010, 2010 17th IEEE International Conference on Electronics, Circuits and Systems.

[33]  John R. Koza,et al.  Genetic programming - on the programming of computers by means of natural selection , 1993, Complex adaptive systems.

[34]  Brunilde Sansò,et al.  A Tabu Search Algorithm for the Location of Data Centers and Software Components in Green Cloud Computing Networks , 2013, IEEE Transactions on Cloud Computing.

[35]  Mauro Birattari,et al.  Dm63 Heuristics for Combinatorial Optimization Ant Colony Optimization Exercises Outline Ant Colony Optimization: the Metaheuristic Application Examples Generalized Assignment Problem (gap) Connection between Aco and Other Metaheuristics Encodings Capacited Vehicle Routing Linear Ordering Ant Colony , 2022 .

[36]  Wen Liu,et al.  Noisy Chaotic Neural Networks With Variable Thresholds for the Frequency Assignment Problem in Satellite Communications , 2008, IEEE Transactions on Systems, Man, and Cybernetics, Part C (Applications and Reviews).

[37]  Lei Zhou,et al.  FPGA segmented channel routing using genetic algorithms , 2005, 2005 IEEE Congress on Evolutionary Computation.

[38]  Lipo Wang,et al.  Solving channel assignment problems using local search methods and simulated annealing , 2011, Defense + Commercial Sensing.

[39]  Kazuyuki Aihara,et al.  Chaotic simulated annealing by a neural network model with transient chaos , 1995, Neural Networks.

[40]  A. Muc.  Buckling Analysis of Laminated Ellipsoidal Shells Subjected to External Pressure , 1991 .

[41]  A. Muc.  Buckling and Postbuckling Behaviour of Imperfect Laminated Shallow Spherical Shells Under External Pressure , 1991 .

[42]  Richard M. Friedberg,et al.  A Learning Machine: Part I , 1958, IBM J. Res. Dev..

[43]  Russell C. Eberhart,et al.  A new optimizer using particle swarm theory , 1995, MHS'95. Proceedings of the Sixth International Symposium on Micro Machine and Human Science.