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An Automatic Heuristic Design Approach for Seru Scheduling Problem with Resource Conflicts
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What this work says
Outgoing claims: the papers this work cites, builds on, or argues with.
inferredcites →https://doi.org/10.1007/11729976_7openalex-snapshot
Dynamic Scheduling with Genetic Programming
inferredcites →https://doi.org/10.1007/978-3-642-01181-8_25openalex-snapshot
Semantic Aware Crossover for Genetic Programming: The Case for Real-Valued Function Regression
inferredcites →https://doi.org/10.1007/978-3-642-12148-7_16openalex-snapshot
Improving the Generalisation Ability of Genetic Programming with Semantic Similarity based Crossover
inferredcites →https://doi.org/10.1007/s10479-020-03850-yopenalex-snapshot
How SERU production system improves manufacturing flexibility and firm performance: an empirical study in China
inferredcites →https://doi.org/10.1016/j.asoc.2016.07.025openalex-snapshot
Adaptive scheduling on unrelated machines with genetic programming
inferredcites →https://doi.org/10.1016/j.asoc.2020.106637openalex-snapshot
Comparison of schedule generation schemes for designing dispatching rules with genetic programming in the unrelated machines environment
inferredcites →https://doi.org/10.1016/j.cie.2016.11.035openalex-snapshot
Line-hybrid seru system conversion: Models, complexities, properties, solutions and insights
inferredcites →https://doi.org/10.1016/j.cie.2019.03.051openalex-snapshot
A hybrid metaheuristic algorithm for a parallel machine scheduling problem with dependent setup times
inferredcites →https://doi.org/10.1016/j.cor.2019.07.016openalex-snapshot
Enriched metaheuristics for the resource constrained unrelated parallel machine scheduling problem
inferredcites →https://doi.org/10.1016/j.ejor.2014.01.029openalex-snapshot
Mathematical analysis and solutions for multi-objective line-cell conversion problem
inferredcites →https://doi.org/10.1016/j.ejor.2017.01.002openalex-snapshot
Models and matheuristics for the unrelated parallel machine scheduling problem with additional resources
inferredcites →https://doi.org/10.1016/j.ejor.2018.05.056openalex-snapshot
Algorithms for the unrelated parallel machine scheduling problem with a resource constraint
inferredcites →https://doi.org/10.1016/j.ejor.2020.09.050openalex-snapshot
A matheuristic for parallel machine scheduling with tool replacements
inferredcites →https://doi.org/10.1016/j.eswa.2019.112915openalex-snapshot
A genetic programming hyper-heuristic approach for the multi-skill resource constrained project scheduling problem
inferredcites →https://doi.org/10.1016/j.eswa.2020.114548openalex-snapshot
Designing dispatching rules with genetic programming for the unrelated machines environment with constraints
inferredcites →https://doi.org/10.1016/j.ijpe.2013.06.009openalex-snapshot
Reducing worker(s) by converting assembly line into a pure cell system
inferredcites →https://doi.org/10.1016/j.jom.2017.01.003openalex-snapshot
Lessons from seru production on manufacturing competitively in a high cost environment
inferredcites →https://doi.org/10.1016/j.jom.2017.02.001openalex-snapshot
Competitive manufacturing in a high‐cost environment: Introduction to the special issue
inferredcites →https://doi.org/10.1016/j.promfg.2020.01.359openalex-snapshot
Job Shop Scheduling by Branch and Bound Using Genetic Programming
inferredcites →https://doi.org/10.1016/j.swevo.2020.100807openalex-snapshot
A genetic programming hyper-heuristic for the distributed assembly permutation flow-shop scheduling problem with sequence dependent setup times
inferredcites →https://doi.org/10.1016/s0305-0548(02)00228-9openalex-snapshot
Genetic search methods in air traffic control
inferredcites →https://doi.org/10.1016/s0925-5273(03)00196-8openalex-snapshot
A heuristic to minimize makespan of cell scheduling problem
inferredcites →https://doi.org/10.1016/s0965-9978(00)00109-5openalex-snapshot
Investigating the use of genetic programming for a classic one-machine scheduling problem
inferredcites →https://doi.org/10.1080/00207543.2017.1284359openalex-snapshot
Line-seru conversion towards reducing worker(s) without increasing makespan: models, exact and meta-heuristic solutions
inferredcites →https://doi.org/10.1080/00207543.2017.1403664openalex-snapshot
The evolution of production systems from Industry 2.0 through Industry 4.0
inferredcites →https://doi.org/10.1080/00207543.2019.1680898openalex-snapshot
Reducing the total tardiness by Seru production: model, exact and cooperative coevolution solutions
inferredcites →https://doi.org/10.1080/0951192x.2012.717717openalex-snapshot
Combining local search into non-dominated sorting for multi-objective line-cell conversion problem
inferredcites →https://doi.org/10.1109/cca.1999.806209openalex-snapshot
Air traffic control using genetic search techniques
inferredcites →https://doi.org/10.1109/cec.1999.785549openalex-snapshot
A genetic programming heuristic for the one-machine total tardiness problem
inferredcites →https://doi.org/10.1109/tase.2019.2895369openalex-snapshot
Automatic Design of Intercell Scheduling Heuristics
inferredcites →https://doi.org/10.1109/tevc.2012.2227326openalex-snapshot
A Computational Study of Representations in Genetic Programming to Evolve Dispatching Rules for the Job Shop Scheduling Problem
inferredcites →https://doi.org/10.1111/poms.12590openalex-snapshot
Knowledge Creation and Dissemination in Operations and Supply Chain Management
inferredcites →https://doi.org/10.1142/s0218213012400192openalex-snapshot
VARIABLE NEIGHBORHOOD DESCENT FOR THE UNRELATED PARALLEL MACHINE SCHEDULING PROBLEM
inferredcites →https://doi.org/10.1145/2576768.2598224openalex-snapshot
Evolving "less-myopic" scheduling rules for dynamic job shop scheduling with genetic programming
inferredcites →https://doi.org/10.1186/s40064-016-2445-5openalex-snapshot
Complexity of line-seru conversion for different scheduling rules and two improved exact algorithms for the multi-objective optimization
inferredcites →https://doi.org/10.1504/ajmsa.2019.110377openalex-snapshot
Consideration of skills in assembly lines and seru production systems
What points at this work
Incoming claims: where this work appears in other papers’ reference lists and arguments.
inferred← citeshttps://doi.org/10.2139/ssrn.4666189openalex-extracted
Scheduling Problems in Seru Production System Considering Worker Cooperation and Learning Behavior
inferred← citeshttps://doi.org/10.1007/s11518-022-5534-8openalex-snapshot
Seru Scheduling Problems with Multiple Due-Windows Assignment and Learning Effect
inferred← citeshttps://doi.org/10.1016/j.ejor.2023.01.022openalex-snapshot
An on-line seru scheduling algorithm with proactive waiting considering resource conflicts
inferred← citeshttps://doi.org/10.1108/aa-04-2022-0087openalex-snapshot
Assembly line-Seru conversion in the C2M enterprise: an empirical study in China
inferred← citeshttps://doi.org/10.17341/gazimmfd.1745136openalex-snapshot
Akıllı SERU sistemleri: DeJong öğrenme etkisi ile çok dönemli üretim planlaması yeniliği
inferred← citeshttps://doi.org/10.3390/pr12010038openalex-snapshot
Optimizing Production Schedules: Balancing Worker Cooperation and Learning Dynamics in Seru Systems
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