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New Frontiers for Optimal Control Applications
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New Frontiers for Optimal Control Applications

A special issue of Information (ISSN 2078-2489). This special issue belongs to the section "Information Systems".

Deadline for manuscript submissions: closed (1 May 2020) | Viewed by 15674

Special Issue Editors

Prof. Dr. Paolo Di Giamberardino

E-Mail Website
Guest Editor
Dept. of Computer, Control and Management Engineering, Sapienza University of Rome, 00185 Roma, Italy
Interests: discrete time and sampled nonlinear dynamics; sensors networks and distributed actuators; modeling and control of viruses spread; optimal control; applications
Prof. Dr. Daniela Iacoviello

E-Mail Website
Guest Editor
Dept. of Computer, Control and Management Engineering, Sapienza University of Rome, 00185 Roma, Italy
Interests: optimal control; epidemic modeling; image analysis

Special Issue Information

Dear Colleagues,

Optimal control theory represents a powerful instrument to determine the best strategy to modify the behavior of a system satisfying operative constraints. While the classical theory is well established, the variety of applications requires continuous improvements in the methodologies and in the consequent numerical implementations.

With the recent improved interest in some modern research fields, optimal control techniques are increasing the range of their effective application, spanning from aerospace to automotive, from process control to fault detection, from traffic control to energy distribution, extending their capabilities to communications, economics, social sciences, life sciences, and human health.

The heterogeneous scenario in which optimal control strategies can be fruitfully adopted, involving various modeling techniques as well as different mathematical tools, brings forth the necessity of introducing new potentialities in the classical theory, thus also producing interesting improvements in the theoretical framework, in the numerical solutions, and in the implementation techniques.

The purpose of this Special Issue is to present the latest developments in optimal control, both from a methodological and application point of view, with particular attention to the new research and development areas in which optimal control techniques can provide promising solutions.

Original research as well as reviews papers are welcome.

Topics of interest include all the modern applications in which optimal control approaches are suitably and successfully introduced.

Prof. Paolo Di Giamberardino
Prof. Daniela Iacoviello
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Information is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

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Published Papers (4 papers)

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Research

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19 pages, 1019 KiB  
Article
Grade Setting of a Timber Logistics Center Based on a Complex Network: A Case Study of 47 Timber Trading Markets in China
by Liang Xue, Xin Huang, Yuchun Wu, Xingchen Yan and Yan Zheng
Information 2020, 11(2), 107; https://doi.org/10.3390/info11020107 - 16 Feb 2020
Cited by 2 | Viewed by 3849
Abstract
The location and grade setting of a timber logistics center is an important link in the optimization of the timber logistics system, the rationality of which can effectively improve the efficiency of the timber logistics supply chain. There is a long distance between [...] Read more.
The location and grade setting of a timber logistics center is an important link in the optimization of the timber logistics system, the rationality of which can effectively improve the efficiency of the timber logistics supply chain. There is a long distance between the main forested areas in China, and more than 55% of the timber demand depends on imports. Research and practice of systematically planning timber logistics centers in the whole country have not been well carried out, which reduces the efficiency of timber logistics. In this paper, 47 timber trading markets with a certain scale in China are selected as the basis for logistics center selection. Based on their transportation network relationship and the number of enterprises in the market, combined with the complex network theory and data analysis method, the network characteristics of three different transportation networks are measured. After determining the transportation capacity indicator, the logistics capacity coefficient is measured based on the freight volume of each node. Then, the important nodes are identified, and each node is graded to systematically set up the timber logistics center. Full article
(This article belongs to the Special Issue New Frontiers for Optimal Control Applications)
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22 pages, 6568 KiB  
Article
A Parameter-Free Outlier Detection Algorithm Based on Dataset Optimization Method
by Liying Wang, Lei Shi, Liancheng Xu, Peiyu Liu, Lindong Zhang and Yanru Dong
Information 2020, 11(1), 26; https://doi.org/10.3390/info11010026 - 31 Dec 2019
Cited by 1 | Viewed by 3563
Abstract
Recently, outlier detection has widespread applications in different areas. The task is to identify outliers in the dataset and extract potential information. The existing outlier detection algorithms mainly do not solve the problems of parameter selection and high computational cost, which leaves enough [...] Read more.
Recently, outlier detection has widespread applications in different areas. The task is to identify outliers in the dataset and extract potential information. The existing outlier detection algorithms mainly do not solve the problems of parameter selection and high computational cost, which leaves enough room for further improvements. To solve the above problems, our paper proposes a parameter-free outlier detection algorithm based on dataset optimization method. Firstly, we propose a dataset optimization method (DOM), which initializes the original dataset in which density is greater than a specific threshold. In this method, we propose the concepts of partition function (P) and threshold function (T). Secondly, we establish a parameter-free outlier detection method. Similarly, we propose the concept of the number of residual neighbors, as the number of residual neighbors and the size of data clusters are used as the basis of outlier detection to obtain a more accurate outlier set. Finally, extensive experiments are carried out on a variety of datasets and experimental results show that our method performs well in terms of the efficiency of outlier detection and time complexity. Full article
(This article belongs to the Special Issue New Frontiers for Optimal Control Applications)
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16 pages, 811 KiB  
Article
Grey Wolf Algorithm and Multi-Objective Model for the Manycast RSA Problem in EONs
by Hejun Xuan, Lidan Lin, Lanlan Qiao and Yang Zhou
Information 2019, 10(12), 398; https://doi.org/10.3390/info10120398 - 17 Dec 2019
Cited by 2 | Viewed by 2620
Abstract
Manycast routing and spectrum assignment (RSA) in elastic optical networks (EONs) has become a hot research field. In this paper, the mathematical model and high efficient algorithm to solve this challenging problem in EONs is investigated. First, a multi-objective optimization model, which minimizes [...] Read more.
Manycast routing and spectrum assignment (RSA) in elastic optical networks (EONs) has become a hot research field. In this paper, the mathematical model and high efficient algorithm to solve this challenging problem in EONs is investigated. First, a multi-objective optimization model, which minimizes network power consumption, the total occupied spectrum, and the maximum index of used frequency spectrum, is established. To handle this multi-objective optimization model, we integrate these three objectives into one by using a weighted sum strategy. To make the population distributed on the search domain uniformly, a uniform design method was developed. Based on this, an improved grey wolf optimization method (IGWO), which was inspired by PSO (Particle Swarm Optimization, PSO) and DE (Differential Evolution, DE), is proposed to solve the maximum model efficiently. To demonstrate high performance of the designed algorithm, a series of experiments are conducted using several different experimental scenes. Experimental results indicate that the proposed algorithm can obtain better results than the compared algorithm. Full article
(This article belongs to the Special Issue New Frontiers for Optimal Control Applications)
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Review

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24 pages, 4064 KiB  
Review
Applications of Nonlinear Programming to the Optimization of Fractionated Protocols in Cancer Radiotherapy
by Alessandro Bertuzzi, Federica Conte, Federico Papa and Carmela Sinisgalli
Information 2020, 11(6), 313; https://doi.org/10.3390/info11060313 - 10 Jun 2020
Cited by 5 | Viewed by 4817
Abstract
The present work of review collects and evidences the main results of our previous papers on the optimization of fractionated radiotherapy protocols. The problem under investigation is presented here in a unitary framework as a nonlinear programming application that aims to determine the [...] Read more.
The present work of review collects and evidences the main results of our previous papers on the optimization of fractionated radiotherapy protocols. The problem under investigation is presented here in a unitary framework as a nonlinear programming application that aims to determine the optimal schemes of dose fractionation commonly used in external beam radiotherapy. The radiation responses of tumor and normal tissues are described by means of the linear quadratic model. We formulate a nonlinear, non-convex optimization problem including two quadratic constraints to limit the collateral normal tissue damages and linear box constraints on the fractional dose sizes. The general problem is decomposed into two subproblems: (1) analytical determination of the optimal fraction dose sizes as a function of the model parameters for arbitrarily fixed treatment lengths; and (2) numerical determination of the optimal fraction number, and of the optimal treatment time, in different parameter settings. After establishing the boundedness of the optimal number of fractions, we investigate by numerical simulation the optimal solution behavior for experimentally meaningful parameter ranges, recognizing the crucial role of some parameters, such as the radiosensitivity ratio, in determining the optimality of hypo- or equi-fractionated treatments. Our results agree with findings of the theoretical and clinical literature. Full article
(This article belongs to the Special Issue New Frontiers for Optimal Control Applications)
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