A Novel Metaheuristics To Solve Mixed Shop Scheduling Problems [PDF]
International Journal in Foundations of Computer Science &
Technology, March2013, Volume 3, Number 2, ISSN : 1839-7662, 2013 This paper represents the metaheuristics proposed for solving a class of Shop Scheduling problem. The Bacterial Foraging Optimization algorithm is featured with Ant Colony Optimization algorithm and proposed as a natural inspired computing approach to solve the Mixed Shop Scheduling problem.
Ravibabu, V.
arxiv +3 more sources
Proposta de classificação hierarquizada dos modelos de solução para o problema de job shop scheduling A proposition of hierarchical classification for solution models in the job shop scheduling problem [PDF]
Gestão & Produção, 1999 Este artigo propõe uma classificação hierarquizada dos modelos utilizados na solução do problema de programação da produção intermitente do tipo job shop, incluindo tanto os que fornecem solução ótima, quanto os modelos heurísticos mais recentes baseados
Ricardo Ferrari Pacheco +1 more
doaj +2 more sources
An Improved Adaptive Neural Network for Job-Shop Scheduling [PDF]
, 2006 This article is posted here with permission of IEEE - Copyright @ 2005 IEEEJob-shop scheduling is one of the most difficult production scheduling problems in industry.
Shengxiang Yang
openalex +6 more sources
Constraint satisfaction adaptive neural network and heuristics combined approaches for generalized job-shop scheduling [PDF]
, 2000 Copyright @ 2000 IEEEThis paper presents a constraint satisfaction adaptive neural network, together with several heuristics, to solve the generalized job-shop scheduling problem, one of NP-complete constraint satisfaction problems.
Shengxiang Yang, Dingwei Wang
openalex +3 more sources
Research on Priority-based Flexible Job Shop Scheduling Algorithm [PDF]
E3S Web of Conferences, 2021 Research on the Flexible Job Shop Scheduling (FJSP) problem in the manufacturing process of aircraft engines has been carried out. It is found that there are real requirements such as order mandatory nodes and equipment selection in the current job ...
Liu Manxing, Xia Xiufeng
doaj +1 more source
A novel method-based reinforcement learning with deep temporal difference network for flexible double shop scheduling problem [PDF]
Scientific ReportsThis paper studies the flexible double shop scheduling problem (FDSSP) that considers simultaneously job shop and assembly shop. It brings about the problem of scheduling association of the related tasks.
Xiao Wang +4 more
doaj +2 more sources
A Research Review on Job Shop Scheduling Problem [PDF]
E3S Web of Conferences, 2021 In recent years, the manufacturing industry has developed rapidly with fierce competition. Manufacturing enterprises are faced with the challenge of on-time delivery, multiple product choices and quick response to order modification.
Yu Yingchen
doaj +1 more source
Flexible Job-Shop Scheduling via Graph Neural Network and Deep Reinforcement Learning
IEEE Transactions on Industrial Informatics, 2023 Recently, deep reinforcement learning (DRL) has been applied to learn priority dispatching rules (PDRs) for solving complex scheduling problems. However, the existing works face challenges in dealing with flexibility, which allows an operation to be ...
Wen Song +3 more
semanticscholar +1 more source
A case study of variational quantum algorithms for a job shop scheduling problem [PDF]
EPJ Quantum Technology, 2021 Combinatorial optimization models a vast range of industrial processes aiming at improving their efficiency. In general, solving this type of problem exactly is computationally intractable.
D. Amaro +4 more
semanticscholar +1 more source
Deep Reinforcement Learning for Dynamic Flexible Job Shop Scheduling with Random Job Arrival
Processes, 2022 The production process of a smart factory is complex and dynamic. As the core of manufacturing management, the research into the flexible job shop scheduling problem (FJSP) focuses on optimizing scheduling decisions in real time, according to the changes
Jingru Chang +4 more
semanticscholar +1 more source