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6篇 您的检索式：作者名="Daryl Essam"

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		题名	作者	年代	出处	被引量
	1	Multi-operator based evolutionary algorithms for solving constrained optimization problems显示文摘	Saber M. Elsayed Ruhul A. Sarker Daryl L. Essam	2011	Computers and Operations Research2011，，12：	1
	2	Solving the ship inventory routing and scheduling problem with undedicated compartments显示文摘	Nurhadi Siswanto Daryl Essam Ruhul Sarier	2011	Computers & Industrial Engineering2011，61，2：	1
	3	Solving the Ship Inventory Routing and Scheduling Problem with Undedicated Compartments显示文摘	Nurhadi Siswanto Daryl Essam Ruhul Sarker	2011	Computers & Industrial Engineering2011，，61：	1
	4	A self-adaptive combined strategies algorithm for constrained optimization using differentialevolution 显示文摘	Saber M Elsayed Ruhul A Sarker Daryl L Essam	2014	Applied Mathematics and Computation2014，241，：	1
	5	A new genetic algorithm for solving optimization problems显示文摘	Saber M Elsayed Ruhul A Sarker Daryl L Essam	2014	Engineering Applications of Artificial Intelligence2014，，27：	1
	6	Interleaving Guidance in Evolutionary Multi-Objective Optimization显示文摘In this paper,we propose a framework that uses localization for multi-objective optimization to simultane- ously guide an evolutionary algorithm in both the decision and objective spaces.The localization is built using a limited number of adaptive spheres(local models)in the decision space.These spheres are usually guided,using some direction information,in the decision space towards the areas with non-dominated solutions.We use a second mechanism to adjust the spheres to specialize on different parts of the Pareto front by using a guided dominance technique in the objective space.Through this interleaved guidance in both spaces,the spheres will be guided towards different parts of the Pareto front while also exploring the decision space efficiently.The experimental results showed good performance for the local models using this dual guidance,in comparison with their original version.	Lam Thu Bui Kalyanmoy Deb Hussein A.Abbass Daryl Essam	2008	Journal of Computer Science & Technology2008，23，1：	0

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