Redirigiendo al acceso original de articulo en 19 segundos...
ARTÍCULO
TITULO

A genetic algorithm and variable neighborhood search for the unrelated parallel machine scheduling problem with sequence dependent setup time

Everton Tozzo    
Syntia Lemos Cotrim    
Edwin Vladimir Cardoza Galdamez    
Gislaine Camila Lapasini Leal (Author)    

Resumen

This paper presents the evaluation of two metaheuristics to solve the Unrelated Parallel Machine Scheduling Problem with Sequence Machine Dependent Setup Time. Considering such a problem, there is no relation between the time to process each task and the machine; and this is why the machines are referred to as unrelated. Furthermore, the setup time between the executions of two tasks depends on both, the task sequence and its associated machine. A metaheuristic genetic algorithm and a variable neighborhood search were used in order to solve the problem due to the difference among their characteristics. The maximal time for the schedule to be completed, also called makespan, was the performance measure used to evaluate the solutions. The results obtained by both metaheuristics were directly compared according to their performance to try to reduce this makespan. The results showed that the variable neighborhood algorithm search outperformed the genetic algorithm regarding the solutions quality and execution time. 

 Artículos similares

       
 
Raymundo Peña-García, Rodolfo Daniel Velázquez-Sánchez, Cristian Gómez-Daza-Argumedo, Jonathan Omega Escobedo-Alva, Ricardo Tapia-Herrera and Jesús Alberto Meda-Campaña    
This research introduces a physics-based identification technique utilizing genetic algorithms. The primary objective is to derive a parametric matrix, denoted as A, describing the time-invariant linear model governing the longitudinal dynamics of an air... ver más
Revista: Aerospace

 
María Elena Tejeda-del-Cueto, Manuel Alberto Flores-Alfaro, Miguel Toledo-Velázquez, Lorena del Carmen Santos-Cortes, José Hernández-Hernández and Marco Osvaldo Vigueras-Zúñiga    
The objective of this study is to develop a genetic algorithm that uses the IGP parameterization to increase the lift coefficient (CL) of three airfoils to be used on wings of unmanned aerial vehicles (UAVs). The geometry of three baseline airfoils was m... ver más
Revista: Aerospace

 
Shuling Zhao and Sishuo Zhao    
Due to the intensification of economic globalization and the impact of global warming, the development of methods to reduce shipping costs and reduce carbon emissions has become crucial. In this study, a multi-objective optimization algorithm was designe... ver más

 
Zhu Wang, Junfeng Cheng and Hongtao Hu    
Port operations have been suffering from hybrid uncertainty, leading to various disruptions in efficiency and tenacity. However, these essential uncertain factors are often considered separately in literature during berth and quay crane assignments, lead... ver más

 
Changping Sun, Mengxia Li, Linying Chen and Pengfei Chen    
Effective utilization of tugboats is the key to safe and efficient transport and service in ports. With the growth of maritime traffic, more and more large seaports show a trend toward becoming super-scale, and are divided into multiple specialized termi... ver más