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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
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Durán Márquez, Mariana
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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
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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
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Fiore, Ugo
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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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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
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;
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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Binary monkey algorithm for approximate packing non-congruent circles in a rectangular container
(2018)
Torres-Escobar, Rafael
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Marmolejo Saucedo, José Antonio
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Litvinchev, Igor
A Packing problem consists in the best arrangement of several objects inside a bounded area named as the container. This arrangement must fulfill with technological constraints, for example, objects should not be overlapping. Some packing models for circular objects are typically formulated as non-convex optimization problems; where the continuous variables are the coordinates of the objects, so they are limited to not finding optimal solutions. Due to the combinatorial nature in the arrangement of such objects, heuristic methods are being used extensively which combine methods of global search and methods of local exhaustive search of local minima or their approximations. In this paper, we will address the packing problem for non-congruent (different size) circles with the binary version of the monkey algorithm which incorporates a cooperation process and a greedy strategy. We use a rectangular grid for covering the container. Every node in the grid represent potential positions for a circle. In this sense, binary monkey algorithm for the knapsack problem, can be used to solve de 0–1 approximate packing problem for non-congruet circles. The binary monkey problem uses two additional processes of the original monkey algorithm, these two processes are a greedy process and a cooperation processes. © 2018, Springer Science+Business Media, LLC, part of Springer Nature.
Scopus© Citations 23 12 1
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Preface: Special Issue on Modeling, Simulation, and Optimization in Operational Research
(2021)
Weber, Gerhard-Wilhelm
;
Thomas, J. Joshua
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Marmolejo Saucedo, José Antonio
;
Fiore, Ugo
;
Litvinchev, Igor
“Operational Research” (OR) is “the discipline of applying advanced analytical methods to help make better decisions”. By using techniques such as problem structuring methods and mathematical modeling to analyze nontrivial situations, OR gives executives the power to make more effective decisions and build more productive systems. The host journal of this special issue, Journal of the Operations Research Society of China (JORSC), is the flagship journal of the Operations Research Society of China. Its primary goal is to promote researches and applications of all aspects of OR. JORSC provides a forum for practioners, academics and researchers in OR and related fields. It reflects the rapid social and economic development of China and leads to new problems and challenges which require new OR methodology and techniques. For closer information about JORSC, we refer to https://www.springer.com/journal/40305/aims-and-scope. © Springer Nature
Scopus© Citations 1 31 2

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