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SPEA2: Improving the Strength Pareto Evolutionary Algorithm For Multiobjective Optimization

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The article was published on 2002-01-01 and is currently open access. It has received 1972 citations till now. The article focuses on the topics: Pareto principle & Multi-objective optimization.

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Formal Methods for System Level Performance Analysis and Optimization

TL;DR: An overview over a formal approach to system level performance modelling and analysis is given to cover distributed multiprocessor systems as well as multiprocessionor systems on chip.
Book ChapterDOI

To DE or Not to DE? Multi-objective Differential Evolution Revisited from a Component-Wise Perspective

TL;DR: This work conducts an iterative analysis on the algorithmic design space, considering DE and environmental selection components as factors, and shows a great level of interaction between algorithm components, indicating that their effectiveness depends on how they are combined.
Proceedings ArticleDOI

Hyperheuristic encoding scheme for multi-objective guillotine cutting problems

TL;DR: Hyperheuristic-based encodings are designed and implemented as an alternative to combine heuristics in such a way that a heuristic's strengths make up for the drawbacks of another in the overall production process.
Journal ArticleDOI

Hybrid organization of functional departments and manufacturing cells in the presence of imprecise data

TL;DR: In this paper, a hybrid shop design problem is formulated as a constrained fuzzy multi-objective optimization problem and an evolutionary programming algorithm is devised to solve it, which is illustrated in test examples.
Book ChapterDOI

Discovering and Navigating a Collection of Process Models Using Multiple Quality Dimensions

TL;DR: In this article, the authors present an extension to the flexible ETM algorithm that does not result in a single best process model but in a collection of mutually non-dominating process models.
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