most citedMulticriteria Optimization and Decision Making: Principles, Algorithms and Case Studies

9 citations · 9 across the 17 of their papers we have counts for

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math.OC2026

Three-Objective Integral R2 Subset Selection: NP-Hardness and Submodular Approximation

Michael T. M. Emmerich

Selecting a fixed number of representative points from a finite Pareto-front approximation is a fundamental post-processing task in multiobjective optimization. This paper studies…

math.OC2026

Optimizing Explicit Unit-Distance Lower-Bound Certificates

Michael T. M. Emmerich

The 2026 disproof of Erdős's unit-distance conjecture and Sawin's quantitative refinement show that the maximum number of unit distances among planar points can exceed $…

math.OC2026

Preference-Shaped Expected Hypervolume and R2 Improvement: Exact Computation and Monotonicity

Michael T. M. Emmerich

This paper studies preference-shaped expected improvement criteria for Bayesian multiobjective optimization. We consider two indicator families which are often used for similar alg…

math.OC2026

Exact Uniform L1 Spacing for Solow-Polasky Diversity on Lines and Ordered Pareto Fronts

Michael T. M. Emmerich, Mahboubeh Nezhadmoghaddam, Jesús Guillermo Falcón Cardona

We study fixed-cardinality maximization of the inverse-matrix Solow--Polasky diversity, equivalently finite metric magnitude for the exponential kernel, on one-dimensional and orde…

math.OC2026

Nonsmooth Set-Gradient Ascent to the Pareto Front via Layered Hypervolume and Magnitude Indicators

Michael T. M. Emmerich

A nonsmooth set-gradient ascent method is developed for moving finite approximation sets toward the Pareto front in multiobjective optimization. The method optimizes layered set in…

math.OC2026

The Magnitude of Dominated Sets: A Pareto Compliant Indicator Grounded in Metric Geometry

Michael T. M. Emmerich

We investigate \emph{magnitude} as a new unary and strictly Pareto-compliant quality indicator for finite approximation sets to the Pareto front in multiobjective optimization. Mag…