A bi-objective branch-and-bound algorithm for the unit-time job shop scheduling : A mixed graph coloring approach

Kouider, Ahmed; Haddadene, Hacene Ait

doi:10.1016/j.cor.2021.105319

Cited by 8 publications

(3 citation statements)

References 42 publications

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“…Some papers aimed at deriving optimal solutions. Among them, branch and bound is a popular exact approach in solving scheduling problems [13,14] with single or multi-objectives [13].…”

Section: Scheduling Problems In Productionmentioning

confidence: 99%

A Generic Model for the Human and AGV-Aided Reconfigurable Flexible Job Shop Scheduling Problems

Chen,

Luo,

Zeng

et al. 2023

Advances in Transdisciplinary Engineering

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Scheduling tasks for workshops has been a critical problem in modern factories, especially when many countries promote the development of Industry 4.0. Nowadays, many factories are shifting to flexible, intelligent manufacturing systems (IMS) to improve their ability to respond to customers’ demands of variation and individualization. Previous job shop scheduling problems always simplified the production scenarios by ignoring the machines’ reconfiguration abilities and the participation of human and automated guided vehicle systems (AGVS), which are critical parts of IMS. To address these issues, this paper derives a novel mix-integer programming model for highly-flexible job shop scheduling models in human and AGV-aided IMS to minimize the makespan. A dataset is generated to examine the effectiveness of our model. Furthermore, we conducted numerical experiments on the dataset. Through experiments and analysis, we explore the interaction between optimal values and key factors, including processing time and machine numbers.

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“…Some papers aimed at deriving optimal solutions. Among them, branch and bound is a popular exact approach in solving scheduling problems [13,14] with single or multi-objectives [13].…”

Section: Scheduling Problems In Productionmentioning

confidence: 99%

A Generic Model for the Human and AGV-Aided Reconfigurable Flexible Job Shop Scheduling Problems

Chen,

Luo,

Zeng

et al. 2023

Advances in Transdisciplinary Engineering

View full text Add to dashboard Cite

show abstract

“…Для прибора M 8 множество Q (8) Для прибора M 9 множество Q (9) целочисленных операций определяет множество V 9 , которое состоит из четырех единичных операций и разбивается на две единичные операции {v 25 , v 26 } требования J 4 и две единичные операции {v 31 , v 32 } требования J 5 . Запрещение одновременного выполнения любой пары операций из множества V 9 задается полным двудольным графом…”

Section: множество дугunclassified

“…Задача поиска оптимальной раскраски c(G) смешанного графа является NP-трудной, даже если A = ∅ [3]. Взаимосвязь задач поиска оптимальных раскрасок смешанного графа с задачами теории расписаний с критерием минимизации длины расписания (минимизации общего времени обслуживания требований) при условии, что все операции обслуживания требований имеют единичные длительности, исследовалась в статьях [4][5][6][7][8]. В [9] представлен обзор опубликованных результатов по раскраскам смешанных графов и эквивалентным задачам построения оптимальных расписаний выполнения операций с единичными длительностями.…”

Section: Introductionunclassified

Оптимальное По Быстродействию Расписание Обслуживания Требований С Прерываниями Операций Как Оптимальная Раскраска Смешанного Графа

2023

Автомат. и телемех.

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A self-learning discrete salp swarm algorithm based on deep reinforcement learning for dynamic job shop scheduling problem

Chen

Wang

2023

Appl Intell

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A bi-objective branch-and-bound algorithm for the unit-time job shop scheduling : A mixed graph coloring approach

Cited by 8 publications

References 42 publications

A Generic Model for the Human and AGV-Aided Reconfigurable Flexible Job Shop Scheduling Problems

A Generic Model for the Human and AGV-Aided Reconfigurable Flexible Job Shop Scheduling Problems

Оптимальное По Быстродействию Расписание Обслуживания Требований С Прерываниями Операций Как Оптимальная Раскраска Смешанного Графа

A self-learning discrete salp swarm algorithm based on deep reinforcement learning for dynamic job shop scheduling problem

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