Stochastic economic lot scheduling via self-attention based deep reinforcement learning
The Stochastic Economic Lot Scheduling Problem (SELSP) is a difficult dynamic optimization problem with wide industrial applications. Traditional methods such as hyper-heuristics are manually designed based on substantial expert knowledge, which may limit their optimization performance. Recently, De...
Saved in:
Main Authors: | SONG, Wen, MI, Nan, LI, Qiqiang, ZHUANG, Jing, CAO, Zhiguang |
---|---|
Format: | text |
Language: | English |
Published: |
Institutional Knowledge at Singapore Management University
2023
|
Subjects: | |
Online Access: | https://ink.library.smu.edu.sg/sis_research/8201 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Institution: | Singapore Management University |
Language: | English |
Similar Items
-
Flexible job-shop scheduling via graph neural network and deep reinforcement learning
by: SONG, Wen, et al.
Published: (2023) -
Deep reinforcement learning guided improvement heuristic for job shop scheduling
by: ZHANG, Cong, et al.
Published: (2024) -
Metaheuristics for the mixed shop scheduling problem
by: Liu, S.Q., et al.
Published: (2014) -
Metaheuristics for the mixed shop scheduling problem
by: Liu, S.Q., et al.
Published: (2014) -
REINFORCEMENT LEARNING BASED SOLUTION APPROACHES FOR INTEGRATED SCHOOL BUS ROUTING AND SCHEDULING PROBLEM
by: EDA KOKSAL AHMED
Published: (2021)