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Agent-Based Simulation Model for Profit Maximization

Year 2016, Volume: 4 Issue: 1, 26 - 33, 16.01.2016

Banu Çalış

https://doi.org/10.17858/jmisci.50792
Cited By: 1

Abstract

Abstract- This study considers a single-machine scheduling problem where the objective is to maximize total profit (Prmax). The problem is identified as 1 ││ Prmax. Aim of this study is to develop a profit based scheduling model using agent-based architecture in order to increase profitability of a single machine manufacturing systems. All objective functions in the literature are based on manufacturing cost, this study shows a new profit based approach to solve single machine scheduling problems. Model is simulated on the hypothetical data and simulation results show that performance of the proposed model is highly acceptable.

Keywords

Scheduling Agent Based Systems Profit Based Scheduling Single Machine

References

  • Agnetis A. & Pacciarelli D. (2007). Multi-agent single machine scheduling, Ann. Oper. Res. 150 3–15.
  • Cheng T.C.E., Ng C.T., & Yuan .J. J. (2006) . Multi-agent scheduling on a single machine to minimize total weighted number of tardy jobs. Theoretical Computer Science 362 273 – 281
  • Cheng S.-R. (2014). Scheduling Two-Agents with a Time-Dependent Deterioration to Minimize the Minsum Earliness Measures. Asia Pac. J. Oper. Res., 31, DOI: 10.1142/S0217595914500407
  • Cowling P. I., Ouelhadj D. & Petrovic S. (2004). Dynamic scheduling of steel casting and milling using multi-agents. Production Planning & Control, Vol. 15, No. 2, 178–188
  • Eren T. (2009). Minimizing the total weighted completion time on a single machine scheduling with release dates and a learning effect. Applied Mathematics and Computation. Vol. 208, Issue 2, pp 355–358
  • Huang C.J. & Liao L.M. (2012). A multi-agent-based negotiation approach for parallel machine scheduling with multi-objectives in an electro-etching process, Int. J. Prod. Res. 50 5719–5733.
  • Janiak A. & Rudek R. (2008). A new approach to the learning effect: Beyond the learning curve restrictions. Comput. Oper. Res. Volume 35, Issue 11, November pp 3727–3736
  • Ji M., He Y.,& Cheng T.C.E. (2007). Single-machine scheduling with periodic maintenance to minimize makespan, Comput. Oper. Res. 34 1764–1770.
  • Liao C.J. & Chen W.J.(2003). Single-machine scheduling with periodic maintenance and nonresumable jobs, Comput. Oper. Res. 30 1335–1347
  • Madejski, J. (2007). Survey of the agent-based approach to intelligent manufacturing. Journal of Achievements in Materials and Manufacturing Engineering, 21(1), 67–70
  • Meirina C., Levchuk G. M., & Pattipati K. R., (2003). A multi-agent decision framework for DDD-III environment,” in Proceedings of the 8th International Command and Control Research and Technology Symposium, June
  • Mosheiov, G., & Yovel, U. (2006). Minimizing weighted earliness–tardiness and duedate cost with unit processing-time jobs. European Journal of Operational Research, 172(2), 528–544
  • Nong Q. Q., Cheng T. C., & Ng C. T. (2011).Two-agent scheduling to minimize the total cost, European Journal of Operational Research, vol. 215, no. 1, pp. 39–44,
  • Ross E. H. P. & Corne D. (2005). Evolutionary Scheduling: A Review, Genetic Programming and Evolvable Machines, 6, 191–220,
  • Shaw M.J. & Whinston A.B. (1983). Distributed planning in cellular flexible manufacturing systems, Technical Report, Management Information Research Center, Purdue University,
  • Sousa, P., & Ramos, C. (1999). A distributed architecture and negotiation protocol for scheduling in manufacturing systems. Computers in Industry, 38(2), 103–113.
  • Walker, S.S., Brennan, R.W., & Norrie, D.H., 2005. Holonic job shop scheduling using a multiagent system. IEEE Intelligent Systems, 20 (1), 50–57.
  • Wu C.C., Wu W.-H., Chen J.-C., Yin Y., &Wu W.H. (2013) A study of the single-machine two-agent scheduling problem with release times. Applied Soft Computing Vol. 13, Issue 2, pp 998–1006
  • Wooldridge M. & Jennings N. R. (1995). Intelligent Agents: Theory and Practice. In Knowledge Engineering Review 10(2),
  • Yin Y., Wu W.-H., Cheng S.-R., Wu C.-C. (2012). An investigation on a two-agent single-machine scheduling problem with unequal release dates Computers and Operations Research, 39 (12) pp. 3062–3073
  • Yu X., Zhang Y., Xu D. & Yin Y. (2013). Single machine scheduling problem with two synergetic agents and piece-rate maintenance Applied Mathematical Modelling, 37 (3) pp. 1390–1399
  • Zhang L.Q., Lu L.F., & Yuan J.J. (2009). Single machine scheduling with release dates and rejection, Eur. J. Oper. Res. 198 975–978

Year 2016, Volume: 4 Issue: 1, 26 - 33, 16.01.2016

Banu Çalış

https://doi.org/10.17858/jmisci.50792
Cited By: 1

Abstract

References

  • Agnetis A. & Pacciarelli D. (2007). Multi-agent single machine scheduling, Ann. Oper. Res. 150 3–15.
  • Cheng T.C.E., Ng C.T., & Yuan .J. J. (2006) . Multi-agent scheduling on a single machine to minimize total weighted number of tardy jobs. Theoretical Computer Science 362 273 – 281
  • Cheng S.-R. (2014). Scheduling Two-Agents with a Time-Dependent Deterioration to Minimize the Minsum Earliness Measures. Asia Pac. J. Oper. Res., 31, DOI: 10.1142/S0217595914500407
  • Cowling P. I., Ouelhadj D. & Petrovic S. (2004). Dynamic scheduling of steel casting and milling using multi-agents. Production Planning & Control, Vol. 15, No. 2, 178–188
  • Eren T. (2009). Minimizing the total weighted completion time on a single machine scheduling with release dates and a learning effect. Applied Mathematics and Computation. Vol. 208, Issue 2, pp 355–358
  • Huang C.J. & Liao L.M. (2012). A multi-agent-based negotiation approach for parallel machine scheduling with multi-objectives in an electro-etching process, Int. J. Prod. Res. 50 5719–5733.
  • Janiak A. & Rudek R. (2008). A new approach to the learning effect: Beyond the learning curve restrictions. Comput. Oper. Res. Volume 35, Issue 11, November pp 3727–3736
  • Ji M., He Y.,& Cheng T.C.E. (2007). Single-machine scheduling with periodic maintenance to minimize makespan, Comput. Oper. Res. 34 1764–1770.
  • Liao C.J. & Chen W.J.(2003). Single-machine scheduling with periodic maintenance and nonresumable jobs, Comput. Oper. Res. 30 1335–1347
  • Madejski, J. (2007). Survey of the agent-based approach to intelligent manufacturing. Journal of Achievements in Materials and Manufacturing Engineering, 21(1), 67–70
  • Meirina C., Levchuk G. M., & Pattipati K. R., (2003). A multi-agent decision framework for DDD-III environment,” in Proceedings of the 8th International Command and Control Research and Technology Symposium, June
  • Mosheiov, G., & Yovel, U. (2006). Minimizing weighted earliness–tardiness and duedate cost with unit processing-time jobs. European Journal of Operational Research, 172(2), 528–544
  • Nong Q. Q., Cheng T. C., & Ng C. T. (2011).Two-agent scheduling to minimize the total cost, European Journal of Operational Research, vol. 215, no. 1, pp. 39–44,
  • Ross E. H. P. & Corne D. (2005). Evolutionary Scheduling: A Review, Genetic Programming and Evolvable Machines, 6, 191–220,
  • Shaw M.J. & Whinston A.B. (1983). Distributed planning in cellular flexible manufacturing systems, Technical Report, Management Information Research Center, Purdue University,
  • Sousa, P., & Ramos, C. (1999). A distributed architecture and negotiation protocol for scheduling in manufacturing systems. Computers in Industry, 38(2), 103–113.
  • Walker, S.S., Brennan, R.W., & Norrie, D.H., 2005. Holonic job shop scheduling using a multiagent system. IEEE Intelligent Systems, 20 (1), 50–57.
  • Wu C.C., Wu W.-H., Chen J.-C., Yin Y., &Wu W.H. (2013) A study of the single-machine two-agent scheduling problem with release times. Applied Soft Computing Vol. 13, Issue 2, pp 998–1006
  • Wooldridge M. & Jennings N. R. (1995). Intelligent Agents: Theory and Practice. In Knowledge Engineering Review 10(2),
  • Yin Y., Wu W.-H., Cheng S.-R., Wu C.-C. (2012). An investigation on a two-agent single-machine scheduling problem with unequal release dates Computers and Operations Research, 39 (12) pp. 3062–3073
  • Yu X., Zhang Y., Xu D. & Yin Y. (2013). Single machine scheduling problem with two synergetic agents and piece-rate maintenance Applied Mathematical Modelling, 37 (3) pp. 1390–1399
  • Zhang L.Q., Lu L.F., & Yuan J.J. (2009). Single machine scheduling with release dates and rejection, Eur. J. Oper. Res. 198 975–978
There are 22 citations in total.

Details

Primary Language English
Authors

Banu Çalış

Publication Date January 16, 2016
Published in Issue Year 2016 Volume: 4 Issue: 1

Cite

APA Çalış, B. (2016). Agent-Based Simulation Model for Profit Maximization. Journal of Management and Information Science, 4(1), 26-33. https://doi.org/10.17858/jmisci.50792
AMA Çalış B. Agent-Based Simulation Model for Profit Maximization. JMISCI. January 2016;4(1):26-33. doi:10.17858/jmisci.50792
Chicago Çalış, Banu. “Agent-Based Simulation Model for Profit Maximization”. Journal of Management and Information Science 4, no. 1 (January 2016): 26-33. https://doi.org/10.17858/jmisci.50792.
EndNote Çalış B (January 1, 2016) Agent-Based Simulation Model for Profit Maximization. Journal of Management and Information Science 4 1 26–33.
IEEE B. Çalış, “Agent-Based Simulation Model for Profit Maximization”, JMISCI, vol. 4, no. 1, pp. 26–33, 2016, doi: 10.17858/jmisci.50792.
ISNAD Çalış, Banu. “Agent-Based Simulation Model for Profit Maximization”. Journal of Management and Information Science 4/1 (January2016), 26-33. https://doi.org/10.17858/jmisci.50792.
JAMA Çalış B. Agent-Based Simulation Model for Profit Maximization. JMISCI. 2016;4:26–33.
MLA Çalış, Banu. “Agent-Based Simulation Model for Profit Maximization”. Journal of Management and Information Science, vol. 4, no. 1, 2016, pp. 26-33, doi:10.17858/jmisci.50792.
Vancouver Çalış B. Agent-Based Simulation Model for Profit Maximization. JMISCI. 2016;4(1):26-33.

Cited By

The role of interoperability of Multi-Agent Systems for IoT applications: A survey on recent advances in smart manufacturing systems
Gazi Üniversitesi Mühendislik-Mimarlık Fakültesi Dergisi
https://doi.org/10.17341/gazimmfd.944264