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Journal articles on the topic 'Minimization makespan'

Author: Grafiati

Published: 4 June 2025

Last updated: 1 August 2025

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1

Pinedo, Michael. "STOCHASTIC BATCH SCHEDULING AND THE “SMALLEST VARIANCE FIRST” RULE." Probability in the Engineering and Informational Sciences 21, no. 4 (2007): 579–95. http://dx.doi.org/10.1017/s0269964807000332.

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Consider a single machine that can process multiple jobs in batch mode. We havenjobs and the processing time of jobjis a random variableXjwith distributionFj. Up tobjobs can be processed simultaneously by the machine. The jobs in a batch all have to start at the same time and the batch is completed when all jobs have finished their processing (i.e., at the maximum of the processing times of the jobs in that batch). We are interested in two objective functions, namely the minimization of the expected makespan and the minimization of the total expected completion time. We first show that under c

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2

K. Sathya Sundari. "Makespan Minimization in Job Shop Scheduling." International Journal of Engineering and Management Research 11, no. 1 (2021): 228–30. http://dx.doi.org/10.31033/ijemr.11.1.31.

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In industries, the completion time of job problems in the manufacturing unit has risen significantly. In several types of current study, the job's completion time, or makespan, is reduced by taking straight paths, which is time-consuming. In this paper, we used an Improved Ant Colony Optimization and Tabu Search (ACOTS) algorithm to solve this problem by precisely defining the fault occurrence location in order to rollback. We have used a short-term memory-based rollback recovery strategy to minimise the job's completion time by rolling back to its own short-term memory. The recent movements i

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3

Dwibedy, Debasis, and Rakesh Mohanty. "Online List Scheduling for Makespan Minimization." ACM SIGACT News 53, no. 2 (2022): 84–105. http://dx.doi.org/10.1145/3544979.3544993.

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In the modern interactive computing era, computational problems such as scheduling, rout- ing, sequencing, and resource management are online in nature. In the online framework, at the outset, an algorithm receives and processes inputs one by one in order without the knowledge of future inputs, unlike in an offline framework, where an algorithm knows the entire input sequence at the beginning. The design of mathematical models and efficient al- gorithms for the online framework constitutes a challenging and competitive area of research in Theoretical Computer Science. The researchers have cons

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4

Happach, Felix. "Makespan minimization with OR-precedence constraints." Journal of Scheduling 24, no. 3 (2021): 319–28. http://dx.doi.org/10.1007/s10951-021-00687-6.

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AbstractWe consider a variant of the NP-hard problem of assigning jobs to machines to minimize the completion time of the last job. Usually, precedence constraints are given by a partial order on the set of jobs, and each job requires all its predecessors to be completed before it can start. In this paper, we consider a different type of precedence relation that has not been discussed as extensively and is called OR-precedence. In order for a job to start, we require that at least one of its predecessors is completed—in contrast to all its predecessors. Additionally, we assume that each job ha

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5

FU, BIN, YUMEI HUO, and HAIRONG ZHAO. "MAKESPAN MINIMIZATION WITH MACHINE AVAILABILITY CONSTRAINTS." Discrete Mathematics, Algorithms and Applications 01, no. 02 (2009): 141–51. http://dx.doi.org/10.1142/s1793830909000129.

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We investigate the problems of scheduling n jobs to m machines with availability constraints. We consider two different models of availability constraints: the preventive model where the unavailability is due to preventive machine maintenance, and the fixed job model where the unavailability is due to a priori assignment of some of the n jobs to certain machines at certain times. In both models, the objective is to minimize the makespan. We assume that m is a constant, and if a job is interrupted by the unavailable interval, it can be resumed after the machine becomes available. For fixed job

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6

Lin, Chien-Hung, and Ching-Jong Liao. "Makespan minimization for multiple uniform machines." Computers & Industrial Engineering 54, no. 4 (2008): 983–92. http://dx.doi.org/10.1016/j.cie.2007.11.009.

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7

Albers, Susanne, and Matthias Hellwig. "Online Makespan Minimization with Parallel Schedules." Algorithmica 78, no. 2 (2016): 492–520. http://dx.doi.org/10.1007/s00453-016-0172-5.

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8

Easwaran, Gopalakrishnan, Larry E. Parten, Rafael Moras, and Paul X. Uhlig. "Makespan minimization in machine dominated flowshop." Applied Mathematics and Computation 217, no. 1 (2010): 110–16. http://dx.doi.org/10.1016/j.amc.2010.05.022.

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9

Ho, Johnny C., and Johnny S. Wong. "Makespan minimization form parallel identical processors." Naval Research Logistics 42, no. 6 (1995): 935–48. http://dx.doi.org/10.1002/1520-6750(199509)42:6<935::aid-nav3220420606>3.0.co;2-d.

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10

Atalay, Berrin, and M. Duran Toksarı. "Job rejection scheduling problems with deterioration and learning effects." Ömer Halisdemir Üniversitesi Mühendislik Bilimleri Dergisi 14, no. 2 (2025): 607–14. https://doi.org/10.28948/ngumuh.1381334.

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In our study, deterioration and the learning effect in the job rejection scheduling environment was considered together. The processing time of the jobs will decrease with the effect of learning, but will also increase with the effect of deterioration. In our study, this situation was examined for four different objectives. These problems are total completion time minimization, makespan minimization and TADC minimization for single machine scheduling problems and parallel machine scheduling problems with makespan minimization. With three different learning rates (0.8, 0.7, 0.6) and two differe

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11

Senapati, Debabrata, Arnab Sarkar, and Chandan Karfa. "HMDS: A Makespan Minimizing DAG Scheduler for Heterogeneous Distributed Systems." ACM Transactions on Embedded Computing Systems 20, no. 5s (2021): 1–26. http://dx.doi.org/10.1145/3477037.

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The problem of scheduling Directed Acyclic Graphs in order to minimize makespan ( schedule length ), is known to be a challenging and computationally hard problem. Therefore, researchers have endeavored towards the design of various heuristic solution generation techniques both for homogeneous as well as heterogeneous computing platforms. This work first presents HMDS-Bl , a list-based heuristic makespan minimization algorithm for task graphs on fully connected heterogeneous platforms. Subsequently, HMDS-Bl has been enhanced by empowering it with a low-overhead depth-first branch and bound bas

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12

Gupta, Anupam, Amit Kumar, Viswanath Nagarajan, and Xiangkun Shen. "Stochastic makespan minimization in structured set systems." Mathematical Programming 192, no. 1-2 (2021): 597–630. http://dx.doi.org/10.1007/s10107-021-01741-z.

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13

Åblad, Edvin, Ann-Brith Strömberg, and Domenico Spensieri. "Exact makespan minimization of unrelated parallel machines." Open Journal of Mathematical Optimization 2 (May 11, 2021): 1–15. http://dx.doi.org/10.5802/ojmo.4.

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14

Liao, Ching-Jong, and Chien-Hung Lin. "Makespan minimization for two uniform parallel machines." International Journal of Production Economics 84, no. 2 (2003): 205–13. http://dx.doi.org/10.1016/s0925-5273(02)00427-9.

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15

Guignard, Monique. "Solving makespan minimization problems with Lagrangean decomposition." Discrete Applied Mathematics 42, no. 1 (1993): 17–29. http://dx.doi.org/10.1016/0166-218x(93)90176-o.

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16

Arora, Shalini, and M. C. Puri. "Minimization of Makespan in Generalized Assignment Problem." OPSEARCH 36, no. 4 (1999): 360–73. http://dx.doi.org/10.1007/bf03398589.

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17

Brueggemann, Tobias, Johann L. Hurink, Tjark Vredeveld, and Gerhard J. Woeginger. "Exponential size neighborhoods for makespan minimization scheduling." Naval Research Logistics (NRL) 58, no. 8 (2011): 795–803. http://dx.doi.org/10.1002/nav.20485.

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18

Bouznif, M., and R. Giroudeau. "Inapproximability and Polynomial-Time Approximation Algorithm for UET Tasks on Structured Processor Networks." Advances in Operations Research 2011 (2011): 1–20. http://dx.doi.org/10.1155/2011/476939.

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We investigate complexity and approximation results on a processor networks where the communication delay depends on the distance between the processors performing tasks. We then prove that there is no heuristic with a performance guarantee smaller than 4/3 for makespan minimization for precedence graph on a large class of processor networks like hypercube, grid, torus, and so forth, with a fixed diameter . We extend complexity results when the precedence graph is a bipartite graph. We also design an efficient polynomial-time -approximation algorithm for the makespan minimization on processor

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19

Joo, Un Gi. "Makespan Minimization Scheduling Problem with Energy-Efficient Turning On/Off Mechanism." Journal of the Korean Institute of Industrial Engineers 44, no. 1 (2018): 1–8. http://dx.doi.org/10.7232/jkiie.2018.44.1.001.

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20

Pande, Sohan Kumar, Priyanka Swain, Sanjib Kumar Nayak, and Sanjaya Kumar Panda. "An Indicator-Based Algorithm for Task Scheduling in Multi-Cloud Environments." International Journal of Cloud Applications and Computing 12, no. 1 (2022): 1–19. http://dx.doi.org/10.4018/ijcac.308274.

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Cloud computing is the ability to scale various resources and services that can be dynamically configured by the cloud service provider (CSP) and delivered on demand by the customers. The objective of most of the task scheduling algorithms is to ensure that the overall processing time of all the tasks (i.e., makespan) is minimized. Here, minimization of makespan in no way guarantees the minimization of execution cost. In indicator-based (IBTS) task scheduling algorithm for the multi-cloud environment, we can outline the significant contributions as the following: (1) IBTS achieves multi-object

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21

Choi, Shiu‐Hong, and James Siu‐Lung Lee. "A sequencing algorithm for makespan minimization in FMS." Journal of Manufacturing Technology Management 15, no. 3 (2004): 291–97. http://dx.doi.org/10.1108/17410380410523515.

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22

Milidiú, Ruy Luiz, Artur Alves Pessoa, and Eduardo Sany Laber. "The complexity of makespan minimization for pipeline transportation." Theoretical Computer Science 306, no. 1-3 (2003): 339–51. http://dx.doi.org/10.1016/s0304-3975(03)00291-3.

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23

Jiang, Yiwei, Yuqing Zhu, Weili Wu, and Deying Li. "Makespan minimization for MapReduce systems with different servers." Future Generation Computer Systems 67 (February 2017): 13–21. http://dx.doi.org/10.1016/j.future.2016.07.012.

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24

Sevastianov, S. V., and G. J. Woeginger. "Makespan minimization in preemptive two machine job shops." Computing 60, no. 1 (1998): 73–79. http://dx.doi.org/10.1007/bf02684330.

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25

Lee, Kangbok, Joseph Y. T. Leung, and Michael L. Pinedo. "Makespan minimization in online scheduling with machine eligibility." Annals of Operations Research 204, no. 1 (2013): 189–222. http://dx.doi.org/10.1007/s10479-012-1271-6.

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26

Zheng, Siqi, and Zhaohui Liu. "Two-Agent Makespan Minimization Problem on Parallel Machines." Journal of Applied Mathematics and Physics 11, no. 06 (2023): 1693–706. http://dx.doi.org/10.4236/jamp.2023.116110.

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27

Lee, Kangbok, Joseph Y. T. Leung, and Michael L. Pinedo. "Makespan minimization in online scheduling with machine eligibility." 4OR 8, no. 4 (2010): 331–64. http://dx.doi.org/10.1007/s10288-010-0149-1.

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28

Ji, Ping, and Lin Li. "Single-Machine Group Scheduling Problems with Variable Job Processing Times." Mathematical Problems in Engineering 2015 (2015): 1–9. http://dx.doi.org/10.1155/2015/758919.

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This paper considers two resource constrained single-machine group scheduling problems. These problems involve variable job processing times (general position-dependent learning effects and deteriorating jobs); that is, the processing time of a job is defined by the function that involves its starting time and position in the group, and groups’ setup time is a positive strictly decreasing continuous function of the amount of consumed resource. Polynomial time algorithms are proposed to optimally solve the makespan minimization problem under the constraint that the total resource consumption do

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29

Prassetiyo, Hendro, and Firda Heryati. "The Effectiveness of Genetic Algorithm, And the CDS Method In Solving Flowshop Scheduling Problems." E3S Web of Conferences 484 (2024): 01008. http://dx.doi.org/10.1051/e3sconf/202448401008.

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Flow shop scheduling problem is considered NP-hard for m machines and n jobs. For such NP-hard combinatorial optimization problems, heuristics play a major role in searching for near-optimal solutions. In this paper we used Genetic Algorithm, and the CDS method for solving flow shop scheduling problem with makespan as the criteria. The objective of this model is to obtain a sequence of jobs and the minimization of the total completion time (makespan). To test the effectiveness of the method, a dataset of case studies is used to compare the makespan values obtained for each method.

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30

Gorgoi, Mircea, and Corneliu Neagu. "Modeling and Simulation of Holonic Meta-Algorithm in Scheduling Process Using PERT Technique − Optimization in Job Shop Scheduling Problem." Applied Mechanics and Materials 760 (May 2015): 199–204. http://dx.doi.org/10.4028/www.scientific.net/amm.760.199.

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In generally scheduling can be viewed as optimization, bound by sequence and resource constrain and the minimization of the makespan is often used as the criterion. In this paper minimization of the makespan or complete time will be used such as an objective function and not the criterion of the decision. The new approach use heuristic elementary priority dispatch rules as the criterion of the decision. This research purpose a new methodology which use a specific elements of PERT techniques to find the optimum solution. New approach establish a solution's space where are find the all solution

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31

Bercher, Pascal, and Conny Olz. "POP ≡ POCL, Right? Complexity Results for Partial Order (Causal Link) Makespan Minimization." Proceedings of the AAAI Conference on Artificial Intelligence 34, no. 06 (2020): 9785–93. http://dx.doi.org/10.1609/aaai.v34i06.6530.

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We study PO and POCL plans with regard to their makespan – the execution time when allowing the parallel execution of causally independent actions. Partially ordered (PO) plans are often assumed to be equivalent to partial order causal link (POCL) plans, where the causal relationships between actions are explicitly represented via causal links. As a first contribution, we study the similarities and differences of PO and POCL plans, thereby clarifying a common misconception about their relationship: There are PO plans for which there does not exist a POCL plan with the same orderings. We prove

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32

Ogunwolu, L., A. Sosimi, and S. Obialo. "MODELING, OPTIMISATION AND ANALYSIS OF RE-ENTRANT FLOWSHOP JOB SCHEDULING WITH FUZZY PROCESSING TIMES." Nigerian Journal of Technology 36, no. 3 (2017): 806–13. http://dx.doi.org/10.4314/njt.v36i3.21.

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This paper presents a makespan minimization of -jobs -machines re-entrant flow shop scheduling problem (RFSP) under fuzzy uncertainties using Genetic Algorithm. The RFSP objective is formulated as a mathematical programme constrained by number of jobs and resources availability with traditional scheduling policies of First Come First Serve (FCFS) and the First Buffer First Serve (FBFS). Jobs processing times were specified by fuzzy numbers and modelled using triangular membership function representations. The modified centroid defuzzification technique was used at different alpha-cuts to obtai

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33

Hua, Jing, Yingqiong Peng, Yilu Xu, Kun Cao, and Jing Jia. "Makespan Minimization for Multiprocessor Real-Time Systems under Thermal and Timing Constraints." Journal of Circuits, Systems and Computers 28, no. 09 (2019): 1950145. http://dx.doi.org/10.1142/s0218126619501457.

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With the continued scaling of the CMOS device, the exponential increase in power density has strikingly elevated the temperature of on-chip systems. In this paper, the problem of allocating and scheduling frame-based real-time applications is addressed to multiprocessors to minimize the makespan under the thermal and timing constraints. The proposed algorithms consist of offline and online components. The offline component assigns the applications accepted at static time to processors in a way that the finish time of processors are balanced. The online component firstly selects the processor w

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34

Li, Xiaoping, Qian Wang, and Cheng Wu. "Heuristic for no-wait flow shops with makespan minimization." International Journal of Production Research 46, no. 9 (2008): 2519–30. http://dx.doi.org/10.1080/00207540701737997.

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35

Koulamas, Christos, and George J. Kyparisis. "Makespan minimization on uniform parallel machines with release times." European Journal of Operational Research 157, no. 1 (2004): 262–66. http://dx.doi.org/10.1016/s0377-2217(03)00243-1.

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36

Bougeret, Marin, Pierre-Francois Dutot, and Denis Trystram. "Moderately exponential approximation for makespan minimization on related machines." Theoretical Computer Science 511 (November 2013): 32–41. http://dx.doi.org/10.1016/j.tcs.2013.03.020.

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37

Epstein, Leah. "A survey on makespan minimization in semi-online environments." Journal of Scheduling 21, no. 3 (2018): 269–84. http://dx.doi.org/10.1007/s10951-018-0567-z.

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38

Regev, Oded. "Priority algorithms for makespan minimization in the subset model." Information Processing Letters 84, no. 3 (2002): 153–57. http://dx.doi.org/10.1016/s0020-0190(02)00264-8.

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39

Choi, Byung-Cheon, Joseph Y. T. Leung, and Michael L. Pinedo. "A note on makespan minimization in proportionate flow shops." Information Processing Letters 111, no. 2 (2010): 77–81. http://dx.doi.org/10.1016/j.ipl.2010.10.016.

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40

Sun, Zheng-Wei, Dan-Yang Lv, Cai-Min Wei, and Ji-Bo Wang. "Flow Shop Scheduling with Shortening Jobs for Makespan Minimization." Mathematics 13, no. 3 (2025): 363. https://doi.org/10.3390/math13030363.

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This paper deals with a two-machine flow shop problem with shortening jobs. A shortening job means that the job’s processing time is a decreasing function of its starting time. The aim is to find a sequence that minimizes the makespan of all the jobs. several dominance properties, some lower bounds, and an initial upper bound are derived, which are applied to propose a branch-and-bound algorithm to solve the problem. We also propose some heuristics and mathematical programming. Computational experiments are conducted to evaluate the performance of the proposed algorithms.

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41

Rodríguez-Espinosa, Daniel Felipe, Daniela Cruz-Vargas, Daniel Esteban Delgado-Merchán, David Hernando Gonzalez-Estupiñán, and Eliana María González-Neira. "NSGA-II simheuristic to solve a multi-objective flexible flow shop problem under stochastic machine breakdowns." Journal of Project Management 9, no. 4 (2024): 493——512. http://dx.doi.org/10.5267/j.jpm.2024.6.002.

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This study proposes a simheuristic that hybridizes NSGA-II with Monte Carlo simulation to address a stochastic flexible flow shop problem featuring stochastic machine breakdowns. In real-world scenarios, machine breakdowns frequently occur, resulting in negative impacts such as time loss, late deliveries, decreased productivity, and order accumulation. Therefore, this study considers the times between failures and times to repair as stochastic parameters. Multiple objectives are concurrently addressed, including expected makespan, expected tardy jobs, and the standard deviation of tardy jobs.

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42

Ramya, G., and M. Chandrasekaran. "Solving Job Shop Scheduling Problem Based on Employee Availability Constraint." Applied Mechanics and Materials 376 (August 2013): 197–206. http://dx.doi.org/10.4028/www.scientific.net/amm.376.197.

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Manufacturing System is enabled with an excellent knowledge on production plan, proper scheduling of machinery process, employee timetabling and labor costs. Heuristic algorithms are developed to bring optimized results in stipulated time with respect to optimum schedule. This article deals with minimizing the maximum completion time (makespan) based on job scheduling and minimization of labor costs based on employee workload with Shuffled Frog Leaping Algorithm and Sheep Flock Heredity Model Algorithm. The labor costs minimization and makespan which is to find a schedule that satisfies the or

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43

K.C.UDAIYAKUMAR, K. C. UDAIYAKUMAR, and M. CHANDRASEKARAN M.CHANDRASEKARAN. "Tabu Search Algorithm For Solving of Job Shop Scheduling with Single Objective - Makespan Minimization." Indian Journal of Applied Research 3, no. 12 (2011): 365–67. http://dx.doi.org/10.15373/2249555x/dec2013/111.

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44

R, SATHIYA SHANTHI, MEGANATHAN R, JAYAKUMAR S, and VIJAYARAGAVAN R. "Solving flow shop scheduling problems with the objective of minimizing TCT when tie occurs." Journal of Computational Mathematica 5, no. 2 (2021): 1–8. http://dx.doi.org/10.26524/cm102.

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Scheduling process arises naturally upon availability of resources through a systematic approach in which prior planning and decisions should be made. Two machine flow shop scheduling problem (FSSP) was solved by Johnson in the mid of 1954 with makespan minimization as objective. Earlier we proposed two algorithms for the makespan objective; in this paper we intend to investigate the same algorithms for the objective of Total Completion Time of all the jobs (TCT). Experimental results had shown that one of our algorithms gives better results than the other two when the machine order is reverse

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45

Lu, Yuan-Yuan, Fei Teng, and Zhi-Xin Feng. "Scheduling Jobs with Truncated Exponential Sum-of-Logarithm-Processing-Times Based and Position-based Learning Effects." Asia-Pacific Journal of Operational Research 32, no. 04 (2015): 1550026. http://dx.doi.org/10.1142/s0217595915500268.

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In this study, we consider a scheduling problem with truncated exponential sum-of-logarithm-processing-times based and position-based learning effects on a single machine. We prove that the shortest processing time (SPT) rule is optimal for the makespan minimization problem, the sum of the θth power of job completion times minimization problem, and the total lateness minimization problem, respectively. For the total weighted completion time minimization problem, the discounted total weighted completion time minimization problem, the maximum lateness minimization problem, we present heuristic a

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46

Zhao, Jian Feng, Xiao Chun Zhu, and Bao Sheng Wang. "Hybrid Flow-Shop Scheduling Method and Simulation Based on Adaptive Genetic Algorithm." Applied Mechanics and Materials 670-671 (October 2014): 1434–38. http://dx.doi.org/10.4028/www.scientific.net/amm.670-671.1434.

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The n-job, k-stage hybrid flow shop problem is one of the general production scheduling problems. Hybrid flow shop (HFS) problems are NP-Hard when the objective is to minimize the makespan .The research deals with the criterion of makespan minimization for the HFS scheduling problems. In this paper we present a new encoding method so as to guarantee the validity of chromosomes and convenience of calculation and corresponding crossover and mutation operators are designed for optimum sequencing. The simulation results show that the Sequence Adaptive Cross Genetic Algorithm (SACGA) is an effectiv

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47

Wu, Weiyuan. "Dispatching Rules-based Optimization of the No-wait Flow Shop Scheduling Problem." Journal of Physics: Conference Series 2587, no. 1 (2023): 012066. http://dx.doi.org/10.1088/1742-6596/2587/1/012066.

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Abstract To improve the productivity of the flow shop, this paper proposes a new mathematical model to describe the scheduling problem of the no-wait flow shop (NWFS) with the minimization makespan as the scheduling objective. In addition, a new dispatching rule PCA-AS is created using the principal component analysis (PCA) algorithm, and PCA-AS is applied to the process of solving the scheduling problem to gain a scheduling strategy with excellent performance. Finally, the paper numerically verifies that PCA-AS outperforms the shortest processing time (SPT) dispatching rule and the first-in-f

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48

Saini, Nisha, and Jitender Kumar. "Mean makespan task scheduling approach for the edge computing environment." Mean makespan task scheduling approach for the edge computing environment 14, no. 4 (2024): 4714–20. https://doi.org/10.11591/ijece.v14i4.pp4714-4720.

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Task scheduling in the edge computing environment poses significant challenges due to its inherent NP-hard nature. Several researchers concentrated on minimizing simple makespan, disregarding the reduction of the mean time to complete all tasks, resulting in uneven distributions of mean completion times. To address this issue, this study proposes a novel mean makespan task scheduling strategy (MMTSS) to minimize simple and mean makespan. MMTSS optimizes the utilization of virtual machine capacity and uses the mean makespan optimization to minimize the pr

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49

Miao, Cuixia, and Juan Zou. "Parallel-Machine Scheduling with Time-Dependent and Machine Availability Constraints." Mathematical Problems in Engineering 2015 (2015): 1–6. http://dx.doi.org/10.1155/2015/956158.

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We consider the parallel-machine scheduling problem in which the machines have availability constraints and the processing time of each job is simple linear increasing function of its starting times. For the makespan minimization problem, which is NP-hard in the strong sense, we discuss the Longest Deteriorating Rate algorithm and List Scheduling algorithm; we also provide a lower bound of any optimal schedule. For the total completion time minimization problem, we analyze the strong NP-hardness, and we present a dynamic programming algorithm and a fully polynomial time approximation scheme fo

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50

Abreu, Levi R., Bruno A. Prata, Jose M. Framinan, and Marcelo S. Nagano. "New efficient heuristics for scheduling open shops with makespan minimization." Computers & Operations Research 142 (June 2022): 105744. http://dx.doi.org/10.1016/j.cor.2022.105744.

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