|
|
|
|
|
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 ...
ver más
|
|
|
|
|
|
|
|
|
|
|
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...
ver más
|
|
|
|
|
|
|
|
|
|
|
Toufik Mzili, Ilyass Mzili, Mohammed Essaid Riffi and Gaurav Dhiman
This paper presents a new hybrid algorithm that combines genetic algorithms (GAs) and the optimizing spotted hyena algorithm (SHOA) to solve the production shop scheduling problem. The proposed GA-SHOA algorithm incorporates genetic operators, such as un...
ver más
|
|
|
|
|
|
|
|
|
|
|
Cheng Liu, Zhujun Si, Jun Hua and Na Jia
The problem of two-dimensional irregular packing involves the arrangement of objects with diverse shapes and sizes within a given area. This challenge arises across various industrial sectors, where effective packing optimization can yield cost savings, ...
ver más
|
|
|
|
|
|
|
|
|
|
|
Nasser Lotfi and Mazyar Ghadiri Nejad
Multi-objective task graph scheduling is a well-known NP-hard problem that plays a significant role in heterogeneous distributed systems. The solution to the problem is expected to optimize all scheduling objectives. Pretty large state-of-the-art algorit...
ver más
|
|
|
|
|
|
|
|
|
|
|
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...
ver más
|
|
|
|
|
|
|
|
|
|
|
José Victor Sá Santos and Napoleão Nepomuceno
The Cutting Stock Problem (CSP) is an optimisation problem that roughly consists of cutting large objects in order to produce small items. The computational effort for solving this problem is largely affected by the number of cutting patterns. In this ar...
ver más
|
|
|
|
|
|
|
|
|
|
|
Athanasios C. Spanos, Sotiris P. Gayialis, Evripidis P. Kechagias and Georgios A. Papadopoulos
In this research, we present a hybrid algorithmic framework and its integration into the precise production scheduling system of a Greek metal forming factory. The system was created as a decision support tool to assist production planners in arranging w...
ver más
|
|
|
|
|
|
|
|
|
|
|
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...
ver más
|
|
|
|
|
|
|
|
|
|
|
Vincenzo Cutello, Georgia Fargetta, Mario Pavone and Rocco A. Scollo
Community detection is one of the most challenging and interesting problems in many research areas. Being able to detect highly linked communities in a network can lead to many benefits, such as understanding relationships between entities or interaction...
ver más
|
|
|
|
|
|