Optimal energy management for multi-microgrid considering demand response programs: A stochastic multi-objective framework
This paper presents a cooperative multi-objective optimization for the networked microgrids
energy management. We introduce the Independence Performance Index (IPI) for the MGs …
energy management. We introduce the Independence Performance Index (IPI) for the MGs …
Robust combinatorial optimization under convex and discrete cost uncertainty
C Buchheim, J Kurtz - EURO Journal on Computational Optimization, 2018 - Elsevier
In this survey, we discuss the state of the art of robust combinatorial optimization under
uncertain cost functions. We summarize complexity results presented in the literature for …
uncertain cost functions. We summarize complexity results presented in the literature for …
K-adaptability in two-stage mixed-integer robust optimization
A Subramanyam, CE Gounaris… - Mathematical Programming …, 2020 - Springer
We study two-stage robust optimization problems with mixed discrete-continuous decisions
in both stages. Despite their broad range of applications, these problems pose two …
in both stages. Despite their broad range of applications, these problems pose two …
On the complexity of robust multi-stage problems with discrete recourse
We study the computational complexity of multi-stage robust optimization problems. Such
problems are formulated with alternating min/max quantifiers and therefore naturally fall into …
problems are formulated with alternating min/max quantifiers and therefore naturally fall into …
Constraint generation for two-stage robust network flow problems
In this paper, we propose new constraint generation (CG) algorithms for solving the two-
stage robust minimum cost flow problem, a problem that arises from various applications …
stage robust minimum cost flow problem, a problem that arises from various applications …
Railway alignment optimization under uncertainty with a minimax robust method
T Song, H Pu, P Schonfeld, J Hu - IEEE Intelligent …, 2022 - ieeexplore.ieee.org
Railway alignment optimization is difficult due to theoretically infinite possible alternatives,
multiple conflicting and hard-to-quantify objectives, as well as large-scale and highly …
multiple conflicting and hard-to-quantify objectives, as well as large-scale and highly …
A framework for inherently interpretable optimization models
M Goerigk, M Hartisch - European Journal of Operational Research, 2023 - Elsevier
With dramatic improvements in optimization software, the solution of large-scale problems
that seemed intractable decades ago are now a routine task. This puts even more real-world …
that seemed intractable decades ago are now a routine task. This puts even more real-world …
Oracle-based algorithms for binary two-stage robust optimization
N Kämmerling, J Kurtz - Computational Optimization and Applications, 2020 - Springer
In this work we study binary two-stage robust optimization problems with objective
uncertainty. We present an algorithm to calculate efficiently lower bounds for the binary two …
uncertainty. We present an algorithm to calculate efficiently lower bounds for the binary two …
Decomposition-based approaches for a class of two-stage robust binary optimization problems
AN Arslan, B Detienne - INFORMS journal on computing, 2022 - pubsonline.informs.org
In this paper, we study a class of two-stage robust binary optimization problems with
objective uncertainty, where recourse decisions are restricted to be mixed-binary. For these …
objective uncertainty, where recourse decisions are restricted to be mixed-binary. For these …
A Lagrangian dual method for two-stage robust optimization with binary uncertainties
A Subramanyam - Optimization and Engineering, 2022 - Springer
This paper presents a new exact method to calculate worst-case parameter realizations in
two-stage robust optimization problems with categorical or binary-valued uncertain data …
two-stage robust optimization problems with categorical or binary-valued uncertain data …