A two-agent one-machine multitasking scheduling problem solving by exact and metaheuristics

This paper studies a single-machine multitasking scheduling problem together with two-agent consideration. The objective is to look for an optimal schedule to minimize the total tardiness of one agent subject to the total completion time of another agent has an upper bound. For this problem, a branch-and-bound method equipped with several dominant properties and a lower bound is exploited to search optimal solutions for small size jobs. Three metaheuristics, cloud simulated annealing algorithm, genetic algorithm, and simulated annealing algorithm, each with three improvement ways, are proposed to find the near-optimal solutions for large size jobs. The computational studies, experiments, are provided to evaluate the capabilities for the proposed algorithms. Finally, statistical analysis methods are applied to compare the performances of these algorithms.

[1]  D. Meyer,et al.  Executive control of cognitive processes in task switching. , 2001, Journal of experimental psychology. Human perception and performance.

[2]  Dietrich Manzey,et al.  Serial or overlapping processing in multitasking as individual preference: Effects of stimulus preview on task switching and concurrent dual-task performance. , 2016, Acta psychologica.

[3]  C. T. Ng,et al.  Two‐agent scheduling on a single sequential and compatible batching machine , 2017 .

[4]  Etienne Koechlin,et al.  Divided Representation of Concurrent Goals in the Human Frontal Lobes , 2010, Science.

[5]  Michael Pinedo,et al.  Scheduling: Theory, Algorithms, and Systems , 1994 .

[6]  Ghasem Moslehi,et al.  A two-agent scheduling problem in a two-machine flowshop , 2018 .

[7]  Juanjo Noguera,et al.  Multitasking on reconfigurable architectures: microarchitecture support and dynamic scheduling , 2004, TECS.

[8]  Ahmed Azab,et al.  Machine scheduling for multitask machining , 2018 .

[9]  Guowu Yang,et al.  Identifying APT Malware Domain Based on Mobile DNS Logging , 2017 .

[10]  T. C. Edwin Cheng,et al.  Two-agent flowshop scheduling to maximize the weighted number of just-in-time jobs , 2017, J. Sched..

[11]  Alessandro Agnetis,et al.  Scheduling Problems with Two Competing Agents , 2004, Oper. Res..

[12]  F. D. Croce,et al.  The two-machine total completion time flow shop problem , 1996 .

[13]  Ali Sadollah,et al.  A review of energy-efficient scheduling in intelligent production systems , 2019, Complex & Intelligent Systems.

[14]  KC DiwasSingh,et al.  Does Multitasking Improve Performance? Evidence from the Emergency Department , 2014, Manuf. Serv. Oper. Manag..

[15]  Gur Mosheiov,et al.  Single machine batch scheduling with two competing agents to minimize total flowtime , 2011, Eur. J. Oper. Res..

[16]  Mostafa Zandieh,et al.  Cloud theory-based simulated annealing approach for scheduling in the two-stage assembly flowshop , 2010, Adv. Eng. Softw..

[17]  T. C. Edwin Cheng,et al.  Multi-agent single-machine scheduling and unrestricted due date assignment with a fixed machine unavailability interval , 2017, Comput. Ind. Eng..

[18]  Wang Yong,et al.  Two-agent scheduling problems on a single-machine to minimize the total weighted late work , 2017, J. Comb. Optim..

[19]  T.C.E. Cheng,et al.  CON/SLK due date assignment and scheduling on a single machine with two agents , 2016 .

[20]  Colin Reeves.  Genetic Algorithms , 2003, Handbook of Metaheuristics.

[21]  T.C.E. Cheng,et al.  Multitasking parallel-machine scheduling with machine-dependent slack due-window assignment , 2018, Int. J. Prod. Res..

[22]  Csaba Kardos,et al.  A constraint model for assembly planning , 2020, Journal of Manufacturing Systems.

[23]  Jonathan Cole Smith,et al.  A Multiple-Criterion Model for Machine Scheduling , 2003, J. Sched..

[24]  C. D. Gelatt,et al.  Optimization by Simulated Annealing , 1983, Science.

[25]  Albert Y. Zomaya,et al.  Evolutionary Scheduling of Dynamic Multitasking Workloads for Big-Data Analytics in Elastic Cloud , 2014, IEEE Transactions on Emerging Topics in Computing.

[26]  Luis A. Ricardez-Sandoval,et al.  A multitasking continuous time formulation for short-term scheduling of operations in multipurpose plants , 2017, Comput. Chem. Eng..

[27]  T.C.E. Cheng,et al.  An exact branch‐and‐price algorithm for multitasking scheduling on unrelated parallel machines , 2019, Naval Research Logistics (NRL).

[28]  Sridhar Seshadri,et al.  Managerial Allocation of Time and Effort: The Effects of Interruptions , 2001, Manag. Sci..

[29]  Chung-Lun Li,et al.  Task scheduling with progress control , 2018 .

[30]  Feifeng Zheng,et al.  Multitasking scheduling problems with a rate-modifying activity , 2017, Int. J. Prod. Res..

[31]  Douglas A. Wolfe,et al.  Nonparametric Statistical Methods , 1973 .

[32]  Clifford Nass,et al.  Cognitive control in media multitaskers , 2009, Proceedings of the National Academy of Sciences.

[33]  Rico Fischer,et al.  Efficient multitasking: parallel versus serial processing of multiple tasks , 2015, Front. Psychol..

[34]  H. Pashler.  Dual-task interference in simple tasks: data and theory. , 1994, Psychological bulletin.

[35]  T.C.E. Cheng,et al.  Multi-agent scheduling problems under multitasking , 2020, Int. J. Prod. Res..

[36]  Srikanth K. Iyer,et al.  Improved genetic algorithm for the permutation flowshop scheduling problem , 2004, Comput. Oper. Res..

[37]  Yunqiang Yin,et al.  Just-in-time scheduling with two competing agents on unrelated parallel machines ☆ , 2016 .

[38]  Victoria. M. Lea,et al.  Describing interruptions, multi-tasking and task-switching in community pharmacy: a qualitative study in England , 2015, International Journal of Clinical Pharmacy.

[39]  John Sum,et al.  Scheduling jobs with multitasking and asymmetric switching costs , 2017, 2017 IEEE International Conference on Systems, Man, and Cybernetics (SMC).

[40]  Jose M. Framiñan,et al.  A common framework and taxonomy for multicriteria scheduling problems with interfering and competing jobs: Multi-agent scheduling problems , 2014, Eur. J. Oper. Res..

[41]  Chung-Lun Li,et al.  Multitasking via alternate and shared processing: Algorithms and complexity , 2016, Discret. Appl. Math..

[42]  Feifeng Zheng,et al.  Algorithms for the joint multitasking scheduling and common due date assignment problem , 2017, Int. J. Prod. Res..

[43]  Gur Mosheiov,et al.  Scheduling problems with two competing agents to minimized weighted earliness-tardiness , 2013, Comput. Oper. Res..

[44]  Yunqiang Yin,et al.  Due date assignment and two-agent scheduling under multitasking environment , 2020, Journal of Combinatorial Optimization.

[45]  Yazid Mati,et al.  A genetic local search algorithm for minimizing total weighted tardiness in the job-shop scheduling problem , 2008, Comput. Oper. Res..

[46]  David E. Meyer,et al.  Executive control of cognitive processes in task switching. , 2001 .

[47]  C. Wickens,et al.  Applied Attention Theory , 2007 .

[48]  Joseph Y.-T. Leung,et al.  The effects of multitasking on operations scheduling , 2015 .

[49]  John Sum,et al.  Analysis on the Effect of Multitasking , 2015, 2015 IEEE International Conference on Systems, Man, and Cybernetics.

[50]  Alessandro Agnetis,et al.  Multiagent Scheduling - Models and Algorithms , 2014 .

[51]  D. Wolfe,et al.  Nonparametric Statistical Methods. , 1974 .

[52]  Robert H. Logie,et al.  Multitasking, working memory and remembering intentions , 2010 .

[53]  Ameur Soukhal,et al.  Two-agent scheduling with agent specific batches on an unbounded serial batching machine , 2014, Journal of Scheduling.

[54]  Aboul Ella Hassanien,et al.  A hybrid SA-MFO algorithm for function optimization and engineering design problems , 2018 .

[55]  Chengbin Chu,et al.  Multitasking scheduling with multiple rate-modifying activities , 2019, Int. Trans. Oper. Res..

[56]  Appasami Govindasamy,et al.  Optimization of Operating Systems towards Green Computing , 2011, Int. J. Comb. Optim. Probl. Informatics.

[57]  Min Chen,et al.  A sufficient condition for planar graphs with girth 5 to be (1, 7)-colorable , 2017, J. Comb. Optim..

[58]  Danyu Bai,et al.  Cloud theory-based simulated annealing for a single-machine past sequence setup scheduling with scenario-dependent processing times , 2020, Complex & Intelligent Systems.

[59]  John H. Holland,et al.  Genetic Algorithms and Adaptation , 1984 .

[60]  Diwas Singh KC,et al.  Does Multitasking Improve Performance? Evidence from the Emergency Department , 2013 .

[61]  Ze-Hao Lai,et al.  Smart augmented reality instructional system for mechanical assembly towards worker-centered intelligent manufacturing , 2020 .