Search Results for author: Michael T. M. Emmerich

Found 4 papers, 1 papers with code

The Hypervolume Indicator Hessian Matrix: Analytical Expression, Computational Time Complexity, and Sparsity

1 code implementation8 Nov 2022 André H. Deutz, Michael T. M. Emmerich, Hao Wang

Also, for the general $m$-dimensional case, a compact recursive analytical expression is established, and its algorithmic implementation is discussed.

Multiobjective Optimization Second-order methods

A Tailored NSGA-III Instantiation for Flexible Job Shop Scheduling

no code implementations14 Apr 2020 Yali Wang, Bas van Stein, Michael T. M. Emmerich, Thomas Bäck

A customized multi-objective evolutionary algorithm (MOEA) is proposed for the multi-objective flexible job shop scheduling problem (FJSP).

Job Shop Scheduling Scheduling

Maximum Volume Subset Selection for Anchored Boxes

no code implementations2 Mar 2018 Karl Bringmann, Sergio Cabello, Michael T. M. Emmerich

It is known that the problem can be solved in polynomial time in the plane, while the best known running time in any dimension $d \ge 3$ is $\Omega\big(\binom{n}{k}\big)$.

Computational Geometry Data Structures and Algorithms F.2.2

Multiobjective Optimization of Classifiers by Means of 3-D Convex Hull Based Evolutionary Algorithm

no code implementations18 Dec 2014 Jiaqi Zhao, Vitor Basto Fernandes, Licheng Jiao, Iryna Yevseyeva, Asep Maulana, Rui Li, Thomas Bäck, Michael T. M. Emmerich

The design of the algorithm proposed in this paper is inspired by indicator-based evolutionary algorithms, where first a performance indicator for a solution set is established and then a selection operator is designed that complies with the performance indicator.

Binary Classification Classification +5

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