Enhanced memetic search for reducing energy consumption in fuzzy flexible job shops

10Citations
Citations of this article
10Readers
Mendeley users who have this article in their library.

Abstract

The flexible job shop is a well-known scheduling problem that has historically attracted much research attention both because of its computational complexity and its importance in manufacturing and engineering processes. Here we consider a variant of the problem where uncertainty in operation processing times is modeled using triangular fuzzy numbers. Our objective is to minimize the total energy consumption, which combines the energy required by resources when they are actively processing an operation and the energy consumed by these resources simply for being switched on. To solve this NP-Hard problem, we propose a memetic algorithm, a hybrid metaheuristic method that combines global search with local search. Our focus has been on obtaining an efficient method, capable of obtaining similar solutions quality-wise to the state of the art using a reduced amount of time. To assess the performance of our algorithm, we present an extensive experimental analysis that compares it with previous proposals and evaluates the effect on the search of its different components.

Cite

CITATION STYLE

APA

García Gómez, P., González-Rodríguez, I., & Vela, C. R. (2023). Enhanced memetic search for reducing energy consumption in fuzzy flexible job shops. Integrated Computer-Aided Engineering, 30(2), 151–167. https://doi.org/10.3233/ICA-230699

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free