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Rocco A. Scollo, Antonio G. Spampinato, Georgia Fargetta, Vincenzo Cutello and Mario Pavone
Disease phenotypes are generally caused by the failure of gene modules which often have similar biological roles. Through the study of biological networks, it is possible to identify the intrinsic structure of molecular interactions in order to identify ...
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Jeffrey O. Agushaka and Absalom E. Ezugwu
A situation where the set of initial solutions lies near the position of the true optimality (most favourable or desirable solution) by chance can increase the probability of finding the true optimality and significantly reduce the search efforts. In opt...
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Neamah S. Radam, Sufyan T. Faraj Al-Janabi and Khalid Sh. Jasim
The multi-controller placement problem (MCPP) represents one of the most challenging issues in software-defined networks (SDNs). High-efficiency and scalable optimized solutions can be achieved for a given position in such networks, thereby enhancing var...
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Michal Berlinski, Eryk Warchulski and Stanislaw Kozdrowski
This paper presents a logistics problem, related to the transport of goods, which can be applied in practice, for example, in postal or courier services. Two mathematical models are presented as problems occurring in a logistics network. The main objecti...
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Francisca Santana Robles, Eva Selene Hernández-Gress, Neil Hernández-Gress and Rafael Granillo Macias
Everyday there are more disasters that require Humanitarian Supply Chain (HSC) attention; generally these problems are difficult to solve in reasonable computational time and metaheuristics (MHs) are the indicated solution algorithms. To our knowledge, t...
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BongJoo Jeong, Jun-Hee Han and Ju-Yong Lee
This study considers a scheduling problem for a flow shop with urgent jobs and limited waiting times. The urgent jobs and limited waiting times are major considerations for scheduling in semiconductor manufacturing systems. The objective function is to m...
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Bonfim Amaro Junior, Marcio Costa Santos, Guilherme Nepomuceno de Carvalho, Luiz Jonatã Pires de Araújo and Placido Rogerio Pinheiro
The problem of efficiently cutting smaller two-dimensional pieces from a larger surface is recurrent in several manufacturing settings. This problem belongs to the domain of cutting and packing (C&P) problems. This study approached a category of C&am...
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Nebojsa Bacanin, Timea Bezdan, Eva Tuba, Ivana Strumberger and Milan Tuba
Computer vision is one of the most frontier technologies in computer science. It is used to build artificial systems to extract valuable information from images and has a broad range of applications in various areas such as agriculture, business, and hea...
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Jesús Alejandro Navarro-Acosta, Irma D. García-Calvillo, Vanesa Avalos-Gaytán and Edgar O. Reséndiz-Flores
In this study, a system for faults detection using a combination of Support Vector Data Description (SVDD) with metaheuristic algorithms is presented. The presented approach is applied to a real industrial process where the set of measured faults is scar...
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Antonino A. Feitosa Neto, Anne M. P. Canuto and João C. Xavier-Junior
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Mirko M. Stojiljkovic, Mladen M. Stojiljkovic and Bratislav D. Blagojevic
In this paper, a methodology for multi-objective optimization of trigeneration plants is presented. It is primarily applicable to the systems for buildings? energy supply characterized by high load variations on daily, weekly and annual bases, as well as...
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Jayashree Piri, Puspanjali Mohapatra, Raghunath Dey, Biswaranjan Acharya, Vassilis C. Gerogiannis and Andreas Kanavos
The efficiency and the effectiveness of a machine learning (ML) model are greatly influenced by feature selection (FS), a crucial preprocessing step in machine learning that seeks out the ideal set of characteristics with the maximum accuracy possible. D...
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Angel A. Juan, Markus Rabe, Majsa Ammouriova, Javier Panadero, David Peidro and Daniel Riera
In the field of logistics and transportation (L&T), this paper reviews the utilization of simheuristic algorithms to address NP-hard optimization problems under stochastic uncertainty. Then, the paper explores an extension of the simheuristics concep...
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Juan F. Gomez, Antonio R. Uguina, Javier Panadero and Angel A. Juan
The capacitated dispersion problem, which is a variant of the maximum diversity problem, aims to determine a set of elements within a network. These elements could symbolize, for instance, facilities in a supply chain or transmission nodes in a telecommu...
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Azad A. Ameen, Tarik A. Rashid and Shavan Askar
Child drawing development optimization (CDDO) is a recent example of a metaheuristic algorithm. The motive for inventing this method is children?s learning behavior and cognitive development, with the golden ratio being employed to optimize the aesthetic...
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Marko Gulic and Martina ?u?kin
In this paper, a hybrid nature-inspired metaheuristic algorithm based on the Genetic Algorithm and the African Buffalo Optimization is proposed. The hybrid approach adaptively switches between the Genetic Algorithm and the African Buffalo Optimization du...
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Fatma S. Alrayes, Sami Dhahbi, Jaber S. Alzahrani, Amal S. Mehanna, Mesfer Al Duhayyim, Abdelwahed Motwakel, Ishfaq Yaseen and Amgad Atta Abdelmageed
The Internet of Drones (IoD) is greatly developed and promotes many civil applications. However, it can still be prone to several security problems which threaten public safety. The issue of security poses further problems upon linking the IoD to the Int...
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Abiodun M. Ikotun and Absalom E. Ezugwu
Automatic clustering problems require clustering algorithms to automatically estimate the number of clusters in a dataset. However, the classical K-means requires the specification of the required number of clusters a priori. To address this problem, met...
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Sara Pérez-Carabaza, Akemi Gálvez and Andrés Iglesias
Ant Colony Optimization (ACO) encompasses a family of metaheuristics inspired by the foraging behaviour of ants. Since the introduction of the first ACO algorithm, called Ant System (AS), several ACO variants have been proposed in the literature. Owing t...
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Monia Hamdi, Inès Hilali-Jaghdam, Manal M. Khayyat, Bushra M. E. Elnaim, Sayed Abdel-Khalek and Romany F. Mansour
Data mining (DM) involves the process of identifying patterns, correlation, and anomalies existing in massive datasets. The applicability of DM includes several areas such as education, healthcare, business, and finance. Educational Data Mining (EDM) is ...
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