Abstract
Cuckoo search (CS) algorithm was found to be efficient in yielding the global optimal value, and this algorithm was found to outperform genetic algorithm (GA) and particle swarm optimization (PSO) techniques. However, the accuracy of CS heavily depends upon the initial solution and its location from the target value and, therefore, it may involve many generations. Furthermore, the evolutionary operators are applied in each generation. This could lead to delay in convergence. To improve the performance of cuckoo search further, an attempt has been made in the present work to propose a modified cuckoo search involving two-stage initialization. Benchmark functions have been used to test the performance of the proposed method. Furthermore, the proposed method has been applied to wire electrical discharge machining (WEDM) process. Inconel-690, a nickel-based superalloy, has extensive applications in aerospace and nuclear power sectors. Although WEDM is one of the advanced machining processes used to machine such hard-to-cut materials, machining data for this material is not available in the literature. The proposed algorithm was found to be accurate and fast as compared to the GA, PSO, and existing cuckoo search. The machining data generated in this work will also be useful to the industry.
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Abbreviations
- ANOVA:
-
Analysis of variance
- BPNN:
-
Back-propagated neural network
- CS:
-
Cuckoo search
- GA:
-
Genetic algorithm
- GP:
-
Genetic programming
- MRR:
-
Material removal rate
- NSGA:
-
Non-dominated sorting genetic algorithm
- PSO:
-
Particle swarm optimization
- RSM:
-
Response surface methodology
- SR, Ra :
-
Surface roughness
- WEDM:
-
Wire electrical discharge machine
- α :
-
Constant generated randomly in between −1 and 1
- D :
-
Diameter of the hole
- d :
-
Diameter of the boss
- Fit p :
-
Fitness value of an individual particle
- I p :
-
Peak current
- Ncv:
-
Number of control variables
- Nhn:
-
Number of host nests
- p, f :
-
Particle or host nest numbers
- p a :
-
Probability for an egg to be identified by host bird
- Ps :
-
Population size
- Pv :
-
Population vector
- s pq :
-
Step size of qth variable for pth particle
- S v :
-
Servo voltage
- T :
-
Machining time
- T off :
-
Pulse off time
- T on :
-
Pulse on time
- W t :
-
Thickness of work piece
- x ij :
-
Value of jth variable in ith particle
- x max j :
-
Upper bound for jth variable
- x min j :
-
Lower bound for jth variable
- x pq (t):
-
Value of qth variable in pth host nest at current generation, t
- x pq (t + 1):
-
Value of qth variable in pth host nest at next generation
- λ:
-
Constant generated randomly in between 1 and 3
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Acknowledgments
Authors are thankful to the DST-SERB of India for the financial assistance to carry out this research work through project No. SR/FTP/ETA-10/2012.
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Technical Editor: Márcio Bacci da Silva.
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Sreenivasa Rao, M., Venkaiah, N. A modified cuckoo search algorithm to optimize Wire-EDM process while machining Inconel-690. J Braz. Soc. Mech. Sci. Eng. 39, 1647–1661 (2017). https://doi.org/10.1007/s40430-016-0568-9
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DOI: https://doi.org/10.1007/s40430-016-0568-9