A hybrid metaheuristic for a semiconductor production scheduling problem with deterioration effect and resource constraints (original) (raw)

Abstract

The scheduling of jobs and resources is challenging in semiconductor production and large-scale integrated circuit design. This paper considers a semiconductor manufacturing alliance where there are several manufacturers with limited resources, and the goal is to minimize the makespan by making decisions on resources allocation, jobs assignment, jobs batching, and batches sequencing. The job processing time is investigated based on a convex resource formulation integrated with the deterioration effect. Jobs in a single batch have the same starting and finishing time. The batch setup time is defined by the time-dependent function. Meanwhile, limited resources can be allocated to jobs to improve the production efficiency in each batch. Focusing on settings where all jobs have been assigned to manufacturers, this paper derives some important structural properties. Then, for the case with a single manufacturer, an optimal schedule rule is established to arrange jobs and resources. Furthermore, a Variable Neighborhood Search algorithm based on the Biogeography-Based Optimization is designed to solve the problem, which is proved to be NP-hard. The computational results show that our algorithm can generate more robust and appropriate schedules compared to other algorithms from the literature.

Access this article

Log in via an institution

Subscribe and save

• Starting from 10 chapters or articles per month
• Access and download chapters and articles from more than 300k books and 2,500 journals
• Cancel anytime View plans

Buy Now

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Similar content being viewed by others

References

• Arroyo JEC, Leung YT (2017) An effective iterated greedy algorithm for scheduling unrelated parallel batch machines with non-identical capacities and unequal ready times. Comput Ind Eng 105:84–100
  Article Google Scholar
• Brimberg J, Mladenović N, Todosijević R, Urošević D (2017) General variable neighborhood search for the uncapacitated single allocation p -hub center problem. Optim Lett 11(2):377–388
  Article Google Scholar
• Cheng TCE, Hsu CJ, Huang YC, Lee WC (2011) Single-machine scheduling with deteriorating jobs and setup times to minimize the maximum tardiness. Comput Oper Res 38(12):1760–1765
  Article Google Scholar
• Cheng TE, Ding Q, Lin BM (2004) A concise survey of scheduling with time-dependent processing times. Eur J Oper Res 152(1):1–13
  Article Google Scholar
• Chai X, Li W, Zhu Y (2021) Online scheduling to minimize maximum weighted flow-time on a bounded parallel-batch machine. Ann Oper Res 298(1):79–93
  Article Google Scholar
• Coffman EG Jr, Garey MR, Johnson DS (1978) An application of bin-packing to multiprocessor scheduling. SIAM J Comput 7(1):1–17
  Article Google Scholar
• Cruz-Chávez MA, Martínez-Rangel MG, Cruz-Rosales MH (2015) Accelerated simulated annealing algorithm applied to the flexible job shop scheduling problem. Int Trans Oper Res 24(5):1119–1137
  Article Google Scholar
• Dan S (2008) Biogeography-based optimization. IEEE Trans Evol Comput 12(6):702–713
  Article Google Scholar
• Fan W, Pei J, Liu X, Pardalos PM, Kong M (2017) Serial-batching group scheduling with release times and the combined effects of deterioration and truncated job-dependent learning. J Glob Optim, pp 1–17
• Fowler JW, Mönch L (2021) A survey of scheduling with parallel batch (p-batch) processing. Eur J Oper Res 298(1):1–24
  Article Google Scholar
• Gafarov ER, Dolgui A (2022) On lower and upper bounds for single machine parallel batch scheduling. Optim Lett. https://doi.org/10.1007/s11590-022-01857-x
  Article Google Scholar
• Gao Y, Yuan J, Ng CT, Cheng TCE (2019) A further study on two-agent parallel-batch scheduling with release dates and deteriorating jobs to minimize the makespan. Eur J Oper Res 273(1):74–81
  Article Google Scholar
• Gawiejnowicz S (2008) Time-dependent scheduling. Springer Science and Business Media, Berlin
  Book Google Scholar
• Geng X, Wang J, Hsu CJ (2018) Flow shop scheduling problem with convex resource allocation and learning effect. J Comput Commun 06(1):239–246
  Article Google Scholar
• Gong W, Cai Z, Ling CX, Li H (2010) A real-coded biogeography-based optimization with mutation. Appl Math Comput 216(9):2749–2758
  Google Scholar
• Graham RL, Lawler EL, Lenstra JK, Kan AHGR (1979) Optimization and approximation in deterministic sequencing and scheduling: a survey. Ann Discrete Math 5(1):287–326
  Article Google Scholar
• Ikura Y, Gimple M (1986) Efficient scheduling algorithms for a single batch processing machine. Oper Res Lett 5(2):61–65
  Article Google Scholar
• Jerald J, Asokan P, Saravanan R (2006) Simultaneous scheduling of parts and automated guided vehicles in an FMS environment using adaptive genetic algorithm. Int J Adv Manuf Technol 29:584–589
  Article Google Scholar
• Ji M, Cheng TE (2010) Scheduling resumable simple linear deteriorating jobs on a single machine with an availability constraint to minimize makespan. Comput Ind Eng 59(4):794–798
  Article Google Scholar
• Lee WC, Wu CC, Chung YH (2008) Scheduling deteriorating jobs on a single machine with release times. Comput Ind Eng 54(3):441–452
  Article Google Scholar
• Marichelvam MK, Geetha M (2021) A memetic algorithm to solve uncertain energy-efficient flow shop scheduling problems. Int J Adv Manuf Technol 115:515–530
  Article Google Scholar
• Mladenović N, Hansen P (1997) Variable neighborhood search. Comput Oper Res 24(11):1097–1100
  Article Google Scholar
• Mladenović N, Todosijević R, Urošević D (2016) Less is more: basic variable neighborhood search for minimum differential dispersion problem. Inf Sci 326:160–171
  Article Google Scholar
• Milenković M, Milosavljevic N, Bojović N, Val., S. (2021) Container flow forecasting through neural networks based on metaheuristics. Oper Res Int Journal 21:965–997
  Article Google Scholar
• Mönch L, Balasubramanian H, Fowler JW, Pfund ME (2005) Heuristic scheduling of jobs on parallel batch machines with incompatible job families and unequal ready times. Comput Oper Res 32(11):2731–2750
  Article Google Scholar
• Monma CL, Schrijver A, Todd MJ, Wei VK (1990) Convex resource allocation problems on directed acyclic graphs: duality, complexity, special cases, and extensions. Math Oper Res 15(4):736–748
  Article Google Scholar
• Oron D (2011) Scheduling a batching machine with convex resource consumption functions. Inf Process Lett 111(19):962–967
  Article Google Scholar
• Oron D (2014) Scheduling controllable processing time jobs in a deteriorating environment. J Oper Res Soc 65(1):49–56
  Article Google Scholar
• Pei J, Liu X, Fan W, Pardalos PM, Lu S (2017a) A hybrid BA-VNS algorithm for coordinated serial-batching scheduling with deteriorating jobs, financial budget, and resource constraint in multiple manufacturers. Omega. https://doi.org/10.1016/j.omega.2017.12.003
  Article Google Scholar
• Pei J, Liu X, Pardalos PM, Fan W, Yang S (2017b) Scheduling deteriorating jobs on a single serial-batching machine with multiple job types and sequence-dependent setup times. Ann Oper Res 249(1–2):175–195
  Article Google Scholar
• Potts CN, Kovalyov MY (2000) Scheduling with batching: A review. Eur J Oper Res 120(2):228–249
  Article Google Scholar
• Shabtay D (2004) Single and two-resource allocation algorithms for minimizing the maximal lateness in a single machine. Comput Oper Res 31(8):1303–1315
  Article Google Scholar
• Shao K, Fan W, Yang Z, Yang S, Pardalos PM (2021) A column generation approach for patient scheduling with setup time and deteriorating treatment duration. Oper Res Int Journal. https://doi.org/10.1007/s12351-021-00620-x
  Article Google Scholar
• Song J, Shi Z, Sun B, Shi L (2015) Treatment planning for volumetric-modulated arc therapy: Model and heuristic algorithms. IEEE Trans Autom Sci Eng 12(1):116–126
  Article Google Scholar
• Wang GG, Hossein Gandomi A, Yang XS, Hossein Alavi A (2014) A novel improved accelerated particle swarm optimization algorithm for global numerical optimization. Eng Comput 31(7):1198–1220
  Article Google Scholar
• Wang XR, Wang JJ (2013) Single-machine scheduling with convex resource dependent processing times and deteriorating jobs. Appl Math Model 37(4):2388–2393
  Article Google Scholar
• Wei CM, Wang JB, Ji P (2012) Single-machine scheduling with time-and-resource-dependent processing times. Appl Math Model 36(2):792–798
  Article Google Scholar
• Xu R, Chen H, Li X (2012) Makespan minimization on single batch-processing machine via ant colony optimization. Comput Oper Res 39(3):582–593
  Article Google Scholar
• Zhang H, Yang Y, Wu F (2022) Just-in-time single-batch-processing machine scheduling. Comput Oper Res 140:105675
  Article Google Scholar
• Zhao C, Hsu CJ, Wu WH, Cheng SR, Wu CC (2016) Note on a unified approach to the single-machine scheduling problem with a deterioration effect and convex resource allocation. J Manuf Syst 38:134–140
  Article Google Scholar
• Zhao F, Qin S, Zhang Y, Ma W, Zhang C, Song H (2019) A hybrid biogeography-based optimization with variable neighborhood search mechanism for no-wait flow shop scheduling problem. Expert Syst Appl 126:321–339
  Article Google Scholar

Download references

Funding

This work is supported by The National Key Research and Development Program of China (2019YFB1705300), the Fundamental Research Funds for the Central Universities of China (JZ2021HGTA0134; JZ2021HGQA0200; JZ2021HGQA0208; JZ2021HGTA0136), Natural Science Foundation of Anhui Province (2108085QG287, 2008085QG341, 1908085MG223), the Key Research and Development Plan of Anhui Province (2022a05020023), the National Natural Science Foundation of China (Nos. 72101071, 72071056, 72101077), Open Research Fund Program of Key Laboratory of Process Optimization and Intelligent Decision-making (Hefei University of Technology), Ministry of Education, Base of Introducing Talents of Discipline to Universities for Optimization and Decision-making in the Manufacturing Process of Complex Product (111 project: B17014).

Author information

Authors and Affiliations

1. School of Management, Hefei University of Technology, Hefei, China
   Shaojun Lu, Zhiping Zhou, Xinbao Liu & Siwen Liu
2. School of Economics and Management, Anhui Normal University, Wuhu, China
   Min Kong
3. Key Laboratory of Process Optimization and Intelligent Decision-Making of Ministry of Education, Hefei, China
   Min Kong
4. Department of Computer Science, University of Texas at Dallas, Richardson, TX, USA
   Siwen Liu

Authors

1. Shaojun Lu
2. Min Kong
3. Zhiping Zhou
4. Xinbao Liu
5. Siwen Liu

Corresponding authors

Correspondence toShaojun Lu, Min Kong or Zhiping Zhou.

Ethics declarations

Conflict of interest

There is no potential conflicts of interest for this work.

Code availability

All algorithms have been implemented in C++ language and executed on an Inter Core 7, 3.6GHZ PC with 8 GB of RAM.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

About this article

Cite this article

Lu, S., Kong, M., Zhou, Z. et al. A hybrid metaheuristic for a semiconductor production scheduling problem with deterioration effect and resource constraints.Oper Res Int J 22, 5405–5440 (2022). https://doi.org/10.1007/s12351-022-00720-2

Download citation

• Received: 23 July 2021
• Revised: 04 May 2022
• Accepted: 12 May 2022
• Published: 17 June 2022
• Version of record: 17 June 2022
• Issue date: November 2022
• DOI: https://doi.org/10.1007/s12351-022-00720-2

Keywords