On the public citation graph

Scheduling Problems in Seru Production System Considering Worker Cooperation and Learning Behavior

0 signed · 26 inferred · view as graph

Inferred edges come from two machine sources: sweeps of open repository metadata (mostly SSRN and Zenodo), and a bulk OpenAlex citation snapshot. Every row below is labelled with the one it came from. Neither is a complete citation index — absence here is not evidence of absence.

Is this your work? Sign in with ORCID and put your name on the claims that are yours.
Claim with ORCID
Reference health. See whether every reference in this work resolves to a known work and none has been retracted — and get a dated CiteStamped badge you can embed.
See reference health

What this work says

Outgoing claims: the papers this work cites, builds on, or argues with.

inferredcites →https://doi.org/10.1007/s00500-023-07846-1openalex-extracted
An exact branch-and-bound algorithm for seru scheduling problems with sequence-dependent setup time
inferredcites →https://doi.org/10.1007/s10479-013-1364-xopenalex-extracted
Strong NP-hardness of scheduling problems with learning or aging effect
inferredcites →https://doi.org/10.1007/s10479-013-1368-6openalex-extracted
Some results of the worst-case analysis for flow shop scheduling with a learning effect
inferredcites →https://doi.org/10.1007/s10479-021-04515-0openalex-extracted
Scheduling problem in seru production system considering DeJong’s learning effect and job splitting
inferredcites →https://doi.org/10.1007/s11518-022-5534-8openalex-extracted
Seru Scheduling Problems with Multiple Due-Windows Assignment and Learning Effect
inferredcites →https://doi.org/10.1007/s42524-019-0028-1openalex-extracted
Review of seru production
inferredcites →https://doi.org/10.1016/j.cie.2018.02.035openalex-extracted
A multi-skilled worker assignment problem in seru production systems considering the worker heterogeneity
inferredcites →https://doi.org/10.1016/j.cie.2021.107354openalex-extracted
An exact solution method for solving seru scheduling problems with past-sequence-dependent setup time and learning effect
inferredcites →https://doi.org/10.1016/j.eswa.2023.121993openalex-extracted
Parallel dynamic NSGA-II with multi-population search for rescheduling of Seru production considering schedule changes under different dynamic events
inferredcites →https://doi.org/10.1016/j.jmse.2021.05.004openalex-extracted
Solving the rotating seru production problem with dynamic multi-objective evolutionary algorithms
inferredcites →https://doi.org/10.1016/j.jom.2017.01.003openalex-extracted
Lessons from seru production on manufacturing competitively in a high cost environment
inferredcites →https://doi.org/10.1016/j.jom.2017.02.001openalex-extracted
Competitive manufacturing in a high‐cost environment: Introduction to the special issue
inferredcites →https://doi.org/10.1016/j.omega.2016.01.013openalex-extracted
Effects of key enabling technologies for seru production on sustainable performance
inferredcites →https://doi.org/10.1016/j.suscom.2023.100900openalex-extracted
Bi-objective energy-efficient scheduling in a seru production system considering reconfiguration of serus
inferredcites →https://doi.org/10.1057/jors.1971.77openalex-extracted
Extension of the Learning Curve — Some Empirical Results
inferredcites →https://doi.org/10.1061/(asce)0733-9496(2003)129:3(210)openalex-extracted
Optimization of Water Distribution Network Design Using the Shuffled Frog Leaping Algorithm
inferredcites →https://doi.org/10.1061/40569(2001)412openalex-extracted
Water Distribution Network Design Using the Shuffled Frog Leaping Algorithm
inferredcites →https://doi.org/10.1080/00140135708964571openalex-extracted
THE EFFECTS OF INCREASING SKILL ON CYCLE TIME AND ITS CONSEQUENCES FOR TIME STANDARDS
inferredcites →https://doi.org/10.1080/00207543.2022.2054744openalex-extracted
An effective heuristic based on 3- opt strategy for seru scheduling problems with learning effect
inferredcites →https://doi.org/10.1080/21681015.2023.2167875openalex-extracted
A genetic-simulated annealing algorithm for stochastic seru scheduling problem with deterioration and learning effect
inferredcites →https://doi.org/10.1109/jsyst.2019.2963222openalex-extracted
Improved Bacterial Foraging Algorithm for Cell Formation and Product Scheduling Considering Learning and Forgetting Factors in Cellular Manufacturing Systems
inferredcites →https://doi.org/10.1111/itor.12014openalex-extracted
An implementation framework for seru production
inferredcites →https://doi.org/10.1155/2021/8166343openalex-extracted
An Automatic Heuristic Design Approach for Seru Scheduling Problem with Resource Conflicts
inferredcites →https://doi.org/10.1504/ijmr.2023.129301openalex-extracted
A hybrid GA-PSO algorithm for seru scheduling problem with dynamic resource allocation
inferredcites →https://doi.org/10.2514/8.155openalex-extracted
Factors Affecting the Cost of Airplanes
inferredcites →https://doi.org/10.3901/jme.2021.17.263openalex-extracted
Hybrid Shuffled Frog-leaping Algorithm for Distributed Flexible Job Shop Scheduling
Editorial review for independent work. ICSAC — the Institute for Complexity Science and Advanced Computing — runs a structured editorial panel for researchers publishing outside journals, and publishes on CiteStamp rails. Submission is free and goes through ORCID: icsacinstitute.org/submit.