Van locatie-afhankelijke naar marge-afhankelijke centrale capaciteitsplanning: een case-study

Ruth Evers
More and more enterprises have factories at geographically scattered locations. This allows them to be closer to their customers, to react more quickly to changes in the market, to adapt their marketing better to the client and to pay lower wages. This shift from production in one factory to production in several factories makes the production-planning a more complex matter than it used to be.

Van locatie-afhankelijke naar marge-afhankelijke centrale capaciteitsplanning: een case-study

More and more enterprises have factories at geographically scattered locations. This allows them to be closer to their customers, to react more quickly to changes in the market, to adapt their marketing better to the client and to pay lower wages. This shift from production in one factory to production in several factories makes the production-planning a more complex matter than it used to be. In this masterproof the following assignment and planning problem will be studied: given a number of orders, decide which orders will be assigned to which factory and plan the assigment of orders to the factories so that the profit will be optimised. An IP-formulation of the problem will be formulated and will be solved optimally with ILOG CPLEX. Moreover, small adaptions to the data and the model will be carried out in order to analyse their influence on the profit.

Bibliografie

 

Chan F.T.S, Chung S.H., Chan P.L.Y. 2006 Application of genetic algorithms with dominant genes in a distributed scheduling problem in flexible manufacturing systems. International Journal of Production Research 44(3) 523-543.
Chan, F.T.S., Chung, S.H., Chan, L.Y., Finke, G., Tiwari, M.K. 2006. Solving distributed FMS scheduling problems subject to maintenance: Genetic algorithms approach. Robotics and Computer-Integrated Manufacturing 22 493–504.
Chen, Z.-L. and Pundoor, G. 2006 Order assignment and scheduling in a supply chain. Operations Research 54 555–572.
Chung, S.H., et al. 2009 A modified genetic algorithm approach for scheduling of perfect maintenance in distributed production scheduling. Engineering Applications of Artificial Intellegence
DiNatale, M. and Stankovic, J.A. 1995 Applicability of simulated annealing methods to real-time
       scheduling and jitter control. In Proceedings of the 16th IEE Real-Time Systems Symposium 190–199.
Herroelen, W.S. 2007. Project and production scheduling. Acco, Leuven
Houtekier, S. 2004. Plannings- en lay-out problematiek bij Echo nv. Eindverhandeling aan de faculteit Economie en Bedrijfswetenschappen.
Jia, H.Z., Nee, A.Y.C., Fuh, J.Y.H., Zhang, Y.F. 2003. A modified genetic algorithm for distributed scheduling problems. Journal of Intelligent Manufacturing 14 351–362.
Jia, H.Z., Fuh, J.Y.H., Nee, A.Y.C., Zhang, Y.F. 2002. Web-based multi-functional scheduling system for a distributed manufacturing environment. Concurrent Engineering: Research and Applications 10(1) 27–39.

Leung, S.C.H., Wu, Y., Lai, K.K. 2003. Multi-site aggregate production planning with multiple objectives: A goal programming approach. Production Planning and Control 14(5) 425–436.

Universiteit of Hogeschool
Handelsingenieur
Publicatiejaar
2009
Kernwoorden
Share this on: