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12篇 您的检索式：作者名="Kusum Deep"

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		题名	作者	年代	出处	被引量
	1	A new crossover operator for real coded genetic algorithms 显示文摘	Deep Kusum Thakur Manoj	2006	Applied Mathematics and Computation (S0096-3003)2006，188，1：	1
	2	A modified binary particleswarm optimization for knapsack problems显示文摘	Jagdish Chand Bansal Kusum Deep	2012	Applied Mathemat-ics and Computation2012，218，11：	1
	3	A new crossover operator for real coded genetic algorithms显示文摘	Kusum Deep Manoj Thakur		0，，：	1
	4	A new crossover opera- tor for real coded genetic algorithms 显示文摘	Kusum Deep Manoj Thakur	2007	Applied Mathematics and Computation2007，188，1：	1
	5	Mean particle swarm optimisation for function optimization显示文摘	KUSUM DEEP JAGDISH CHAND BANSAL		0，，01：	1
	6	A Modified Binary Parti- cle Swarm Optimization for Knapsack Problems 显示文摘	Jagdish Chand Bansal Kusum Deep	2012	Applied Mathemat- ics and Computation2012，218，11：	1
	7	A new crossover operator for real coded genetic algorithms显示文摘	Kusum Deep Manoj Thakur	2006	Applied Mathematics and Computation2006，，1：	1
	8	A state of art review on application of nature inspired optimization algorithms in protein - ligand docking 显示文摘	Shashi Kusum Deep Katiyar V K Katiyar C K	2009	Indian Journal of Biomechanics : Special Issue2009，，3：	1
	9	Constrained Optimiza- tion Using Gravitational Search Algorithm 显示文摘	Anupam Yadav Kusum Deep	2013	Nation- al Academy Science Letters2013，36，5：	1
	10	Optimal coordination of over-current relays using modified differential evolution algorithms显示文摘	Radha Thangaraj Millie Pant Kusum Deep	2010	Engineering Applications of Artificial Intelligence2010，23，：	1
	11	An interactive method using genetic algorithm for multi-objective optimization problems modeled in fuzzy environment 显示文摘	Kusum Deep Krishna Pratap Singh Kansal M L	2011	Expert System with Applications2011，38，：	1
	12	Gompertz PSO variants for Knapsack and Multi-Knapsack Problems显示文摘Particle Swarm Optimization,a potential swarm intelligence heuristic,has been recognized as a global optimizer for solving various continuous as well as discrete optimization problems.Encourged by the performance of Gompertz PSO on a set of continuous problems,this works extends the application of Gompertz PSO for solving binary optimization problems.Moreover,a new chaotic variant of Gompertz PSO namely Chaotic Gompertz Binary Particle Swarm Optimization(CGBPSO)has also been proposed.The new variant is further analysed for solving binary optimization problems.The new chaotic variant embeds the notion of chaos into GBPSO in later stages of searching process to avoid stagnation phenomena.The efficiency of both the Binary PSO variants has been tested on different sets of Knapsack Problems(KPs):0-1 Knapsack Problem(0-1 KP)and Multidimensional Knapsack Problems(MKP).The concluding remarks have made on the basis of detailed analysis of results,which comprises the comparison of results for Knapsack and Multidimensional Knapsack problems obtained using BPSO,GBPSO and CGBPSO.	Pinkey Chauhan Millie Pant Kusum Deep	2021	Applied Mathematics(A Journal of Chinese Universities)2021，36，4：	0

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