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Deep Learning for Medical Decision Support Systems : Foreword
(Springer Singapore, 2021)
Marmolejo Saucedo, José Antonio
;
Litvinchev, Igor
In this book, different medical data handling techniques are used to develop medical decision support systems in the context of diagnosis perspective. The objective is to use all available information in the decision-making to improve the quality of medical care and to help less experienced doctors in diagnostics.
28 2
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Optimized Filling of a Given Cuboid with Spherical Powders for Additive Manufacturing
(2020)
Duriagina, Zoya
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Lemishka, Igor
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Litvinchev, Igor
;
Durán Márquez, Mariana
;
Pankratov, Alexander
In additive manufacturing (also known as 3D printing), a layer-by-layer buildup process is used for manufacturing parts. Modern laser 3D printers can work with various materials including metal powders. In particular, mixing various-sized spherical powders of titanium alloys is considered most promising for the aerospace industry. To achieve desired mechanical properties of the final product, it is necessary to maintain a certain proportional ratio between different powder fractions. In this paper, a modeling approach for filling up a rectangular 3D volume by unequal spheres in a layer-by-layer manner is proposed. A relative number of spheres of a given radius (relative frequency) are known and have to be fulfilled in the final packing. A fast heuristic has been developed to solve this special packing problem. Numerical results are compared with experimental findings for titanium alloy spherical powders. The relative frequencies obtained by using the imposed algorithm are very close to those obtained by the experiment. This provides an opportunity for using a cheap numerical modeling instead of expensive experimental study. © Springer Nature
Scopus© Citations 31 7 1
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Monkey Algorithm for Packing Circles with Binary Variables
(2018)
Torres Escobar, Rafael
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Marmolejo Saucedo, José Antonio
;
Litvinchev, Igor
;
Vasant, Pandian
The problem of packing non-congruent circles within a rectangular container is considered. The objective is to place the maximum number of circles inside the container such that no circle overlaps with another one. This problem is known to be NP-Hard. Dealing with these problems efficiently is difficult, so heuristic-based methods have been used. In this paper the problem of packing non-congruent circles is solved using the binary version of monkey algorithm. The proposed algorithm uses a grid for approximating the container and considering the grid points as potential positions for assigning centers of the circles. The algorithm consists of five main routines: the climb process, watch-jump process, repairing process, cooperation process and somersault process. Numerical results on packing non-congruent circles are presented to demonstrate the efficiency of the proposed approach. © Springer Nature
Scopus© Citations 7 6 2
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Review on recent implementations of multiobjective and multilevel optimization in sustainable energy economics
(2022)
Ganesan, Timothy
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Litvinchev, Igor
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Marmolejo Saucedo, José Antonio
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Thomas, J. Joshua
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Vasant, Pandian
Rapid progress is currently being made globally in the sustainable energy industry. This trend has been seen to concentrate on specific focus areas in the global energy ecosystem. The integration of sustainability ideas into the existing energy ecosystem has given rise to various complexities, e.g., multilevel and multiobjective (MO) scenarios. This in return has generated various avenues for the implementation of mathematical optimization as well as state-of-the-art operations research methodologies on such real-world systems. This chapter aims to provide a concise review on recent implementations of MO and multilevel optimization on sustainable energy economic systems. Three key industrial areas are given emphasis—economic load/emission dispatch, bioenergy supply chains, and sustainable capacity planning. © 2022 Elsevier Inc. All rights reserved.
Scopus© Citations 1 18 1
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Correction to: Preface: Special Issue on Modeling, Simulation, and Optimization in Operational Research
(2022)
Weber, Gerhard-Wilhelm
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Thomas, J. Joshua
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Marmolejo Saucedo, José Antonio
;
Fiore, Ugo
;
Litvinchev, Igor
The original online version of this article was revised: Modifications have been made to the number of articles mentioned in the preface. © Springer Nature
10 2
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Decomposition Algorithm for Irregular Placement Problems
(2019)
Romanova, T.
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Stoyan, Yu
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Pankratov, A.
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Litvinchev, Igor
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Marmolejo Saucedo, José Antonio
A placement problem of irregular 2D&3D objects in a domain (container) of minimum area (volume), that related to the field of Packing and Cutting problems is considered. Placement objects may be continuously translated and rotated. A general nonlinear programming model of the problem is presented employing the phi-function technique. We propose a decomposition algorithm that generalizes previously published compaction algorithms of searching for local optimal solutions for some packing and cutting problems. Our decomposition algorithm reduces the optimization placement problem to a sequence of nonlinear programming subproblems of considerably smaller dimension. © 2020, Springer Nature Switzerland AG.
Scopus© Citations 22 11 2
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Optimized Packing of Object Clusters with Balancing Conditions
(2020)
Romanova, T.
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Pankratov, A.
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Litvinchev, Igor
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Marmolejo Saucedo, José Antonio
Packing clusters composed of non-overlapping non-identical convex objects is considered. The packing problem, originally stated in Romanova et al. (Math Probl Eng 2019:Article ID 4136430, 12 pages, 2019), is extended here by introducing balancing (equilibrium) conditions. Packing clusters into a rectangular container is considered. Objects in the cluster are of the same shape and allowed to be continuously translated and rotated subject to maximum distance between clusters. This problem is referred to as a sparse equilibrium packing of clusters and formulated as a nonlinear optimization problem. An algorithmic approach to find a locally optimal solution is developed. Computational results are presented to support efficiency of the method for packing clusters with and without balancing conditions. © Springer Nature Switzerland AG 2020.
24 1
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Correction to: Data Analysis and Optimization for Engineering and Computing Problems
(2020)
Vasant, Pandian
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Litvinchev, Igor
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Marmolejo Saucedo, José Antonio
;
;
This book was inadvertently published without updating the following (or with the following error) © Springer Nature Switzerland AG 2020
37 6
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An Optimized Covering Spheroids by Spheres
(2020)
Pankratov, Alexander
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Romanova, Tatiana
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Litvinchev, Igor
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Serrano Bautista, Ramona
Covering spheroids (ellipsoids of revolution) by different spheres is studied. The research is motivated by packing non-spherical particles arising in natural sciences, e.g., in powder technologies. The concept of an ε-cover is introduced as an outer multi-spherical approximation of the spheroid with the proximity ε. A fast heuristic algorithm is proposed to construct an optimized ε-cover giving a reasonable balance between the value of the proximity parameter ε and the number of spheres used. Computational results are provided to demonstrate the efficiency of the approach.
Scopus© Citations 14 14 1
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Balanced Circular Packing Problems with Distance Constraints
(2022)
Romanova, Tetyana
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Pankratov, Olexandr
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Litvinchev, Igor
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Stetsyuk, Petro
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Lykhovyd, Oleksii
The packing of different circles in a circular container under balancing and distance conditions is considered. Two problems are studied: the first minimizes the container’s radius, while the second maximizes the minimal distance between circles, as well as between circles and the boundary of the container. Mathematical models and solution strategies are provided and illustrated with computational results. © 2022 by the authors. Licensee MDPI, Basel, Switzerland.
Scopus© Citations 5 8 1

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