In this paper, we briefly review the development of ranking and selection (R&S) in the past
70 years, especially the theoretical achievements and practical applications in the past 20 …

This article surveys the most relevant kriging-based infill algorithms for multiobjective
simulation optimization. These algorithms perform a sequential search of so-called infill …

For intelligent risk prediction and optimization in the shield tunnel excavation under
uncertainty, this paper proposes a data-driven decision support framework based on the …

CityCOVID is a detailed agent-based model that represents the behaviors and social
interactions of 2.7 million residents of Chicago as they move between and colocate in 1.2 …

Abstract Throughout its history, Operational Research has evolved to include methods,
models and algorithms that have been applied to a wide range of contexts. This …

The use of kriging metamodels in simulation optimization has become increasingly popular
during recent years. The majority of the algorithms so far uses the ordinary (deterministic) …

In healthcare, the planning and the management of resources are challenging as there are
always many complex and stochastic factors in both demand and supply. Simulation …

The availability of assets crucially depends on the interplay between the facility locations,
workforce planning, and capacity allocation. Therefore, in this paper, we model and solve a …

Hyperparameter optimization constitutes a large part of typical modern machine learning
(ML) workflows. This arises from the fact that ML methods and corresponding preprocessing …

Abstract The Winter Simulation Conference serves as the initial publication venue for many
advances in ranking and selection (R&S), including the recently developed R&S procedures …