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Titlebook: Optimization and Decision Science; ODS, Virtual Confere Raffaele Cerulli,Mauro Dell‘Amico,Antonio Sforza Book 2021 The Editor(s) (if applic

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41#
發(fā)表于 2025-3-28 14:53:34 | 只看該作者
Xiaochen Chou,Dominic Loske,Matthias Klumpp,Luca Maria Gambardella,Roberto Montemanniescent dyes, or other chemical modifiers. Three different ways of genetic engineering are described and by these means, peptides are successfully expressed not only when the foot and mouth disease virus (FMDV) 2A sequence or a flexible glycine–serine linker is included, but also when the peptide is
42#
發(fā)表于 2025-3-28 19:59:48 | 只看該作者
43#
發(fā)表于 2025-3-29 00:00:42 | 只看該作者
44#
發(fā)表于 2025-3-29 06:04:48 | 只看該作者
Integer Programming Reformulations in Interval Linear Programmingptimal value range problem, which is NP-hard for general interval linear programs. For this problem, we compare the obtained reformulation with the traditionally used orthant decomposition and also with the non-linear absolute-value formulation that serves as a basis for both of the former approaches.
45#
發(fā)表于 2025-3-29 11:05:37 | 只看該作者
Optimal Improvement of Communication Network Congestion via Nonlinear Programming with Generalized Nnce the equilibrium has been reached, maximizes the aggregate utility and minimizes the sum of delays at the links. We model this problem as a nonlinear knapsack problem with generalized Nash equilibrium constraints and show some preliminary numerical experiments.
46#
發(fā)表于 2025-3-29 13:45:23 | 只看該作者
A Two-Stage Variational Inequality for Medical Supply in Emergency Managementzation problems and reach a stable state governed by the stochastic generalized Nash equilibrium concept. Moreover, we formulate the problem as a two-stage variational inequality. We also present an alternative two-stage variational inequality formulation using the Lagrangian relaxation approximation.
47#
發(fā)表于 2025-3-29 18:15:30 | 只看該作者
48#
發(fā)表于 2025-3-29 21:55:48 | 只看該作者
An Optimization Model for Managing Reagents and Swab Testing During the COVID-19 Pandemicmaximize the quantity of all analyzed swabs while minimizing the time required to obtain the swabs result, the costs due to increase the number of swabs analyzed per unit time and the cost to transfer swabs between laboratories (when a laboratory receives more swab tests than it can analyze).
49#
發(fā)表于 2025-3-30 02:36:29 | 只看該作者
Modelling and Solving Patient Admission and Hospital Stay Problemsolve a set of benchmark instances characterized by real-world features. The experimental results show that the solution approach is effective and allows to obtain optimal/sub-optimal solutions in short computational times.
50#
發(fā)表于 2025-3-30 07:20:38 | 只看該作者
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