Wednesday , April 24 2024

A Framework for Improving Planning-Scheduling Collaboration in Industrial Production Environment

Centro de Investigacion de Gestion e Ingenieria de la Produccion, Universidat Politecnica de Valencia, Cno. de Vera s/n,
Valencia, 46022, Spain

Francisco-Cruz LARIO
Centro de Investigacion de Gestion e Ingenieria de la Produccion, Universidat Politecnica de Valencia, Cno. de Vera s/n,
Valencia, 46022, Spain

Ruben-Dario FRANCO
Centro de Investigacion de Gestion e Ingenieria de la Produccion, Universidat Politecnica de Valencia, Cno. de Vera s/n,
Valencia, 46022, Spain

Centro de Investigacion de Gestion e Ingenieria de la Produccion, Universidat Politecnica de Valencia, Cno. de Vera s/n,
Valencia, 46022, Spain

Abstract: The work presented in this paper highlights how a real scheduling problem can be considered as a process avoiding the traditional operation research-based approach. Understanding the scheduling problem as a dynamic, uncertain and continuous process, in order to reduce the gap between reality and academic models, new conceptual elements emerge. The framework includes methodologies, concepts, architecture, and algorithms, which are based on the idea of a multiagent system in which planning-scheduling relationship is the core proposal. From the framework a software platform has been developed and tested in real industry.

Keywords: Planning-Scheduling collaboration, Framework, Multiagent.

>>Full text
Pedro GÓMEZ-GASQUET, Francisco-Cruz LARIO, Ruben-Dario FRANCO, Victor ANAYA-FONS, A Framework for Improving Planning-Scheduling Collaboration in Industrial Production Environment, Studies in Informatics and Control, ISSN 1220-1766, vol. 20 (1), pp. 67-78, 2011.

1. Introduction

The objective of this paper is to present a modelling approach integrating conceptual models, architectures, methodologies and algorithms in the area of production scheduling. The scheduling problem exists not only in manufacturing enterprises, but also in public and service oriented organizations. It is typically NP-hard.

Problem representation and problem solution are strongly interconnected but each one has its own ways. In the paper we present a framework for collaborative production scheduling and we show how problem description and problem solution can be integrated. To achieve this we follow the Agent-based modelling paradigm.

Agent-based modelling has its roots in Artificial Intelligence (AI) and is further development in the area of Software Engineering. Essential for this kind of frameworks are efficient algorithms to find the problem solution. For the domain of production scheduling algorithms are mainly development at the border of two areas, Operations Research (OR) and Computer Science.

The remainder work is divided according to the following form: the second section review the background, the third section analyses the problem of collaborative scheduling, the fourth section deployed the framework proposed, and fifth section is dedicated to comment implementation and testing of proposed framework. The paper ends with a conclusion about the aforementioned information.


  1. BLAZEWICZ, J., K. ECKER, G. SCHMIDT, J. WEGLARZ, Scheduling in Computer and Manufacturing Systems. Springer, Berlin, 1993.
  2. BIUNDO, S., R. AYLETT, M. BEETZ, D. BORRAJO, A. CESTA, T. GRANT, L. KCCLUSKEY, A. MILANI, VERFAILLIE, G., Technological Roadmap on IA Planning and Scheduling. Planet (in AI Planning), 2003.
  3. BRANDIMARTE, P., M. RIGODANZA, L. ROERO, Conceptual Modeling and Object-oriented Scheduling Architecture Based on Shifting Bottleneck Procedure. IIE Transactions, vol. 32(10), 2000, pp. 921-929.
  4. DAOUAS, T., K. GHEDIRA, J. P. MULLER, How to Schedule a Flow Shop Plant by Agents, in Applications of Artificial Intelligence in Engineering, Billerica, MA: Computational Mechanics Inc., 1995, pp. 73-80.
  5. ESPRIT Consortium AMICE. CIMOSA, 1993, Open System Architecture for CIM.
  6. FRAMIÑAN, J. M., R. RUIZ, Architecture of Manufacturing Scheduling Systems: Literature Review and an Integrated Proposal, European Journal of Operational Research, vol. 205, 2010, pp. 237-246.
  1. GÓMEZ-GASQUET, P., R. RODRIGUEZ-RODRIGUEZ, R. D. FRANCO, A. ORTIZ, A Collaborative Scheduling GA for Products-packages Service within Extended Selling Chains Environment, Journal of Intelligent Manufacturing, 2010 DOI 10.1007/s10845-010-0434-z
  2. GOMEZ-GASQUET, P., Programación de la producción en un taller de flujo híbrido sujeto a incertidumbre: arquitectura y algoritmos. Aplicación a la industria cerámica, Dtors. Lario-Esteban, F. C., Andres-Romano C. UPV, 2010,
  3. GOMEZ-GASQUET, P., C. ANDRES, J. P. GARCÍA-SABATER, Dynamic Hybrid Flow-Shop Scheduling with Due Dates and Sequence Dependent Setup Times, Production Planning and Scheduling (PMS ’04), Nancy, France. Proceedings, 2004, pp. 254-259.
  4. GUPTA, J. N. D., Flowshop Schedules with Sequence Dependent Setup Times, Journal of the Operations Research Society of Japan, vol. 29(3), 1986, pp. 206-219.
  5. S. H., H. C. ZHANG, M. L. SMITH, A Progressive Approach for the Integration of Process Planning and Scheduling, IEE Trans., vol. 27(4), 1995, pp. 456-464.
  6. KEMPENAERS, J., J. PINTE, J. DETAND, J. P. KRUTH, A Collaborative Process Planning and Scheduling System, Advanced Engineering Software, vol. 25(1), 1996, pp. 3-8
  7. KOSANKE, K., Cimosa – Overview and Status, Computers in Industry, vol. 27(2), 1995, pp. 101-109.
  8. LIU, J., K. P. SYCARA, Distributed Problem Solving through Coordination in a Society of Agents, 13th Intl. Workshop on DAI, 1994.
  9. MAMALIS, A. G., I. MALAGARDIS, K. KANBOURIS, Online Integration of Process Planning Module with Production Scheduling, International Journal of Advanced Manufacturing Technology, vol. 12(5), 1996, pp. 330-338.
  10. MONCH, L., Scheduling Framework for Jobs on Parallel Machines in Complex Manufacturing Systems, Wirtschaftsinformatik, vol. 46(6), 2004, pp. 470-480.
  11. PAVON, J., J. GOMEZ-SANZ, Agent Oriented Software Engineering with INGENIAS. Multi-Agent Systems and Applications II, Proceedings, 2691, 2003, pp. 394-403.
  12. PINEDO, M. L., Planning and Scheduling in Manufacturing and Services. Third ed. Springer, Berlin, 2007.
  13. RAJKUMAR, R., P. SHAHABUDEEN, P. NAGARAJ, S. ARUNACHALAM, T. PAGE, A BiCriteria Approach to the M-machine Flowshop Scheduling Problem, Studies in Informatics and Control, Vol. 18(2), 2009, pp. 127-136.
  14. RELVAS, S., H. A. MATOS, A. P. F. D. BARBOSA-POVOA, J. FIALHO, Reactive Scheduling Framework for a Multiproduct Pipeline with Inventory Management, Industrial & Engineering Chemistry Research, vol. 46(17), 2007, pp. 5659-5672.
  15. SCHIEGG, P., Bibliography on Multi-Agent Scheduling in Manufacturing Systems.,
  16. SCHMIDT, G., Modelling Production Scheduling Systems, International Journal of Production Economics, vol. 46, 1996, pp. 109-118.
  17. SHAKERI, S., R. LOGENDRAN, A Mathematical Programming-based Scheduling Framework for Multitasking Environments, European Journal of Operational Research, vol. 176(1), 2007, pp. 193-209.
  18. SHEN, W., Distributed Manufacturing Scheduling using Intelligent Agents, IEEE Expert/Intell. Syst., vol. 17(1), 2002, pp. 88-94.
  19. SMITH, S., Is Scheduling a Solved Problem? The Next Ten Years of Scheduling Research, Cowling, P. and Kendall, G. Ed. San Francisco, CA, 2001, pp. 116-120.
  20. SUN, D., L. LIN, A Dynamic Job-Shop Scheduling Framework – A Backward Approach, International Journal of Production Research, vol. 32(4), 1994, pp. 967-985.
  21. WADHWA, S., J. MADAAN, R. RAINA, A Genetic Algorithm Based Application for a Flexible System, Studies in Informatics and Control, vol. 16(2), 2007, pp. 171-184.
  22. WANG, L., W. SHEN, DPP: An Agent-based Approach for Distributed Process Planning, Journal of Intelligent Manufacturing, vol. 14(5), 2003, pp. 429-440.
  23. WOOLDRIGE, M., N. R. JENNINGS, Intelligent Agents: Theory and Practice, Knowledge Engineering Review, vol. 10(2), 1995, pp. 115-152.
  24. ZELM, M., F. VERNADAT, K. KOSANKE, The CIMOSA business Modelling Process, Computers in Industry, vol. 21(2), 1995, pp.123-142.
  25. ZWEBEN, M., M. S. FOX, Intelligent Scheduling, Morgan Kaufmann, San Francisco, CA, 1994.