Journal ArticleDOI
jMetal: A Java framework for multi-objective optimization
Juan J. Durillo,Antonio J. Nebro +1 more
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TLDR
This paper describes jMetal, an object-oriented Java-based framework aimed at the development, experimentation, and study of metaheuristics for solving multi-objective optimization problems, and includes two case studies to illustrate the use of jMetal in both solving a problem with a metaheuristic and designing and performing an experimental study.About:
This article is published in Advances in Engineering Software.The article was published on 2011-10-01. It has received 1025 citations till now. The article focuses on the topics: Metaheuristic & Multi-objective optimization.read more
Citations
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Book ChapterDOI
A Global Search Approach for Inducing Oblique Decision Trees Using Differential Evolution
TL;DR: Experimental results obtained show that this approach induces more accurate classifiers than those produced by other proposed induction methods.
Journal ArticleDOI
Extracting knowledge for product form design by using multiobjective optimisation and rough sets
Yongfeng Li,Liping Zhu +1 more
Journal ArticleDOI
Evolutionary sensor allocation for the Space Surveillance Network
TL;DR: Simulations show that both the EAT and MOEA approaches effectively use priority in the core tasking algorithms to ensure that higher priority satellites are tracked.
Journal ArticleDOI
RODE: Ranking-Dominance-Based Algorithm for Many-Objective Optimization with Opposition-Based Differential Evolution
TL;DR: This paper presents the RODE algorithm as a novel scalable approach for many-objective problems which adopts the ranking-dominance relation for evaluating the fitness of solutions that provides improved convergence and diversity of solutions.
Book ChapterDOI
Multi-objective Design of Time-Constrained Bike Routes Using Bio-inspired Meta-heuristics
Eneko Osaba,Javier Del Ser,Javier Del Ser,Miren Nekane Bilbao,Pedro Lopez-Garcia,Antonio J. Nebro +5 more
TL;DR: The objective of this approach is to produce a set of Pareto-optimal bike routes that balance the trade-off between the length of the route and its safety level, the latter blending together the slope of the different street segments encompassing the routes and their average road velocity.
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.
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
Muiltiobjective optimization using nondominated sorting in genetic algorithms
N. Srinivas,Kalyanmoy Deb +1 more
TL;DR: Goldberg's notion of nondominated sorting in GAs along with a niche and speciation method to find multiple Pareto-optimal points simultaneously are investigated and suggested to be extended to higher dimensional and more difficult multiobjective problems.
Book
Evolutionary algorithms for solving multi-objective problems
TL;DR: This paper presents a meta-anatomy of the multi-Criteria Decision Making process, which aims to provide a scaffolding for the future development of multi-criteria decision-making systems.
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