An Effective Marine Predators Algorithm for Flexible Job-shop Scheduling Problem

The Flexible Job-shop Scheduling Problem (FJSP) is an extension of the well-known job- shop problem (JSP), where each job can be completed on a machine to optimize several per- formance indicators, including job tardiness, machine utilization, and makespan. It is classified as an NP-hard problem due to its complexity in assigning operations to machines and determining their optimal sequence and real-world applicability. This paper introduces the Marine Predators Algorithm (MPA) for solving the FJSP to minimize the makespan. The performance of the pro- posed MPA was determined by comparing its results to five other metaheuristic algorithms. We perform extensive analyses using the Brandimarte benchmark dataset. The results demonstrate that the MPA outperforms HLO-PSO in key instances, such as MK01 and MK05, with makespan reductions of up to 13%. Our GitHub Link for the Code and Dataset: https://github.com/Noha-Warda/Solving-FJSP-Using-Marine-Predators-Algorithm

Authors

Institutions

Publication Details

Published
2024-11-13
DOI
https://doi.org/10.1109/miucc62295.2024.10783595
Citations
1
Primary Topic
Scheduling and Optimization Algorithms
Type
article
Field-Weighted Citation Impact
0.35
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

An Effective Marine Predators Algorithm for Flexible Job-shop Scheduling Problem

Ahmed El-Sawy, Mohamed Ghoneimy, Noha Warda
1 citations
Scheduling and Optimization Algorithms
0.35
article

An Effective Marine Predators Algorithm for Flexible Job-shop Scheduling Problem

Ahmed El-Sawy, Mohamed Ghoneimy, Noha Warda
article en
1 citations

Abstract

The Flexible Job-shop Scheduling Problem (FJSP) is an extension of the well-known job- shop problem (JSP), where each job can be completed on a machine to optimize several per- formance indicators, including job tardiness, machine utilization, and makespan. It is classified as an NP-hard problem due to its complexity in assigning operations to machines and determining their optimal sequence and real-world applicability. This paper introduces the Marine Predators Algorithm (MPA) for solving the FJSP to minimize the makespan. The performance of the pro- posed MPA was determined by comparing its results to five other metaheuristic algorithms. We perform extensive analyses using the Brandimarte benchmark dataset. The results demonstrate that the MPA outperforms HLO-PSO in key instances, such as MK01 and MK05, with makespan reductions of up to 13%. Our GitHub Link for the Code and Dataset: https://github.com/Noha-Warda/Solving-FJSP-Using-Marine-Predators-Algorithm

October University of Modern Sciences and Arts (EG)
Decent work and economic growth
Openalex Percentile: Top 32%
Scheduling and Optimization Algorithms
0.35
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

An Effective Marine Predators Algorithm for Flexible Job-shop Scheduling Problem — Ahmed El-Sawy, Mohamed Ghoneimy, et al. · (2024) | TGRS Research Map | TGRS