Journal ArticleDOI
Multiobjective cuckoo search for design optimization
Xin-She Yang,Suash Deb +1 more
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TLDR
A new cuckoo search for multiobjective optimization is formulated and applied to solve structural design problems such as beam design and disc brake design.About:
This article is published in Computers & Operations Research.The article was published on 2013-06-01. It has received 729 citations till now. The article focuses on the topics: Metaheuristic & Cuckoo search.read more
Citations
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Proceedings ArticleDOI
New teaching-learnig based optimization algotithm with random local search: TLBO-RLS
TL;DR: A new improved version of Teatching Learnning Based Optimization algorithm, TLBO, is proposed, which includes inclusion of the Bat Algorithm, BA, random local search part in the optimization process with TLBO algorithm.
Placement Compelled Steering Algorithm for Wire length Minimization in FPGA
S L Khaavya,S. Umamaheswari +1 more
TL;DR: Main objective is to provide minimization in wire length during the task placement inside Reconfigurable FPGAs, which will decrease the area, power and delay and increase the speed of execution.
Book ChapterDOI
Generating Distributed Query Plans Using Modified Cuckoo Search Algorithm
T. V. Vijay Kumar,Monika Yadav +1 more
TL;DR: Experimental based comparison of DQPG mCSA with the existing GA based D QPG algorithm (DQPG GA ) shows that the former is able to generate comparatively better quality Top-K query plans, which, in turn, would result in a reduction in the query response time and thereby enabling efficient decision making.
Journal ArticleDOI
Optimum pricing of smart home appliances based on carbon emission and system cost
Jingran Zhen,Majid Khayatnezhad +1 more
TL;DR: In this paper , a model based on a multi-objective mixed-integer program is presented for smart home scheduling with economic and environmental considerations, where one of the objective functions minimizes the operational cost of the building, whereas, the other one minimizes carbon release.
References
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Journal ArticleDOI
A fast and elitist multiobjective genetic algorithm: NSGA-II
TL;DR: This paper suggests a non-dominated sorting-based MOEA, called NSGA-II (Non-dominated Sorting Genetic Algorithm II), which alleviates all of the above three difficulties, and modify the definition of dominance in order to solve constrained multi-objective problems efficiently.
Proceedings ArticleDOI
Particle swarm optimization
TL;DR: A concept for the optimization of nonlinear functions using particle swarm methodology is introduced, and the evolution of several paradigms is outlined, and an implementation of one of the paradigm is discussed.
Book
Multi-Objective Optimization Using Evolutionary Algorithms
Kalyanmoy Deb,Deb Kalyanmoy +1 more
TL;DR: This text provides an excellent introduction to the use of evolutionary algorithms in multi-objective optimization, allowing use as a graduate course text or for self-study.
Journal ArticleDOI
Multiobjective evolutionary algorithms: a comparative case study and the strength Pareto approach
Eckart Zitzler,Lothar Thiele +1 more
TL;DR: The proof-of-principle results obtained on two artificial problems as well as a larger problem, the synthesis of a digital hardware-software multiprocessor system, suggest that SPEA can be very effective in sampling from along the entire Pareto-optimal front and distributing the generated solutions over the tradeoff surface.
Journal ArticleDOI
MOEA/D: A Multiobjective Evolutionary Algorithm Based on Decomposition
Qingfu Zhang,Hui Li +1 more
TL;DR: Experimental results have demonstrated that MOEA/D with simple decomposition methods outperforms or performs similarly to MOGLS and NSGA-II on multiobjective 0-1 knapsack problems and continuous multiobjectives optimization problems.