This article surveys the most relevant kriging-based infill algorithms for multiobjective simulation optimization. These algorithms perform a sequential search of so-called infill …
Y Pan, L Zhang - Automation in Construction, 2022 - Elsevier
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 …
J Ozik, JM Wozniak, N Collier… - … Journal of High …, 2021 - journals.sagepub.com
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) …
L Wang, E Demeulemeester - Iise Transactions, 2023 - Taylor & Francis
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 …
SR Hunter, BL Nelson - Advances in Modeling and Simulation: Seminal …, 2017 - Springer
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 …