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Janis S. Neufeld
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2020 – today
- 2025
- [j13]Jiong-Yu Chen, Quan-Ke Pan, Janis S. Neufeld, Zhong-Hua Miao:
Optimization of task assignment for multi-farm multi-weeding robots based on discrete artificial bee colony algorithm. Expert Syst. Appl. 267: 126182 (2025) - 2024
- [j12]Benedikt Zipfel, Janis S. Neufeld, Udo Buscher:
An iterated local search for customer order scheduling in additive manufacturing. Int. J. Prod. Res. 62(3): 605-625 (2024) - [j11]Julius Hoffmann, Janis S. Neufeld, Udo Buscher:
Minimizing the earliness-tardiness for the customer order scheduling problem in a dedicated machine environment. J. Sched. 27(6): 525-543 (2024) - [i1]Florian Linß, Mike Hewitt, Janis S. Neufeld, Udo Buscher:
Order acceptance and scheduling in capacitated job shops. CoRR abs/2411.19363 (2024) - 2023
- [j10]Janis S. Neufeld, Sven Schulz, Udo Buscher:
A systematic review of multi-objective hybrid flow shop scheduling. Eur. J. Oper. Res. 309(1): 1-23 (2023) - [j9]Xuan He, Quan-Ke Pan, Liang Gao, Janis S. Neufeld:
An asymmetric traveling salesman problem based matheuristic algorithm for flowshop group scheduling problem. Eur. J. Oper. Res. 310(2): 597-610 (2023) - [c4]Paul Päprer, Janis S. Neufeld, Udo Buscher:
A Bi-Objective Column Generation Approach for Real-World Rolling Stock Circulation Planning Problems. ICCL 2023: 350-364 - 2022
- [j8]Liji Shen, Stéphane Dauzère-Pérès, Janis S. Neufeld:
Corrigendum to: "Solving the flexible job shop scheduling problem with sequence-dependent setup times", [European Journal of Operational Research 265, 503-516, 2018]. Eur. J. Oper. Res. 296(2): 748 (2022) - 2021
- [j7]Janis S. Neufeld, Martin Scheffler, Felix Tamke, Kirsten Hoffmann, Udo Buscher:
An efficient column generation approach for practical railway crew scheduling with attendance rates. Eur. J. Oper. Res. 293(3): 1113-1130 (2021) - [c3]Benedikt Zipfel, Janis S. Neufeld, Udo Buscher:
Customer Order Scheduling in an Additive Manufacturing Environment. APMS (4) 2021: 101-109 - 2020
- [j6]Janis S. Neufeld, F. F. Teucher, Udo Buscher:
Scheduling flowline manufacturing cells with inter-cellular moves: non-permutation schedules and material flows in the cell scheduling problem. Int. J. Prod. Res. 58(21): 6568-6584 (2020) - [c2]Martin Scheffler, Janis Sebastian Neufeld:
Daily Distribution of Duties for Crew Scheduling with Attendance Rates: A Case Study. ICCL 2020: 371-383 - [e1]Janis S. Neufeld, Udo Buscher, Rainer Lasch, Dominik Möst, Jörn Schönberger:
Operations Research Proceedings 2019, Selected Papers of the Annual International Conference of the German Operations Research Society (GOR), Dresden, Germany, September 4-6, 2019. Springer 2020, ISBN 978-3-030-48438-5 [contents]
2010 – 2019
- 2019
- [j5]Patrick Zschech, Kai Heinrich, Raphael Bink, Janis S. Neufeld:
Prognostic Model Development with Missing Labels - A Condition-Based Maintenance Approach Using Machine Learning. Bus. Inf. Syst. Eng. 61(3): 327-343 (2019) - [c1]Janis S. Neufeld, Felix J. Schmidt, Tommy Schultz, Udo Buscher:
Capacitated Lot Sizing for Plastic Blanks in Automotive Manufacturing Integrating Real-World Requirements. OR 2019: 539-544 - 2018
- [j4]Liji Shen, Stéphane Dauzère-Pérès, Janis Sebastian Neufeld:
Solving the flexible job shop scheduling problem with sequence-dependent setup times. Eur. J. Oper. Res. 265(2): 503-516 (2018) - 2017
- [j3]Kirsten Hoffmann, Udo Buscher, Janis Sebastian Neufeld, Felix Tamke:
Solving Practical Railway Crew Scheduling Problems with Attendance Rates. Bus. Inf. Syst. Eng. 59(3): 147-159 (2017) - [j2]Armin Klausnitzer, Janis S. Neufeld, Udo Buscher:
Scheduling dynamic job shop manufacturing cells with family setup times: a simulation study. Logist. Res. 10(1): 4 (2017) - 2016
- [b1]Janis Sebastian Neufeld:
Problem specific heuristics for group scheduling problems in cellular manufacturing. University of Dresden, Germany, 2016 - [j1]Janis Sebastian Neufeld, Jatinder N. D. Gupta, Udo Buscher:
A comprehensive review of flowshop group scheduling literature. Comput. Oper. Res. 70: 56-74 (2016)
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last updated on 2025-01-21 00:03 CET by the dblp team
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