Abstract
In this work the authors present a Decision Support System (DSS) for planning daily operations in the sugar cane supply chain. The supply chain model is based on a mixed integer linear programming model. The model objective is to minimize transportation costs while assuring cane supply to the sugar mill. The model determines the fields to harvest, the cutting-loading-transport means for such operation, and the roster for each employee. The DSS has been tested under Cuban conditions but easily can be adapted to different situations updating the parameters of the model. Reported savings represent an 8 % of the fuel cost.
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Díaz, J. A., & Pérez, I. G. (2000). Simulation and optimization of sugar cane transportation in harvest season. In The proceedings of winter simulation conference, Miami, December 2000 (pp. 1114–1117).
Higgins, A. J. (1999). Optimizing cane supply decisions within a sugar mill region. Journal of Scheduling, 2, 229–244.
Higgins, A. J. (2002). Australian sugar mills optimize harvester rosters to improve production. Interfaces, 32(3), 15–25.
Higgins, A. J., & Laredo, L. A. (2006). Improving harvesting and transport planning within a sugar value chain. Journal of the Operational Research Society, 57(4), 367–376.
Higgins, A. J., & Muchow, R. C. (2003). Assessing the potential benefits of alternative cane supply arrangements in the Australian sugar industry. Agricultural Systems, 76, 623–638.
Higgins, A. J., Thorburn, P., Archer, A., & Jakku, E. (2007). Opportunities for value chain research in sugar industries. Agricultural Systems, 94, 611–621.
López, E., Miquel, S., & Plà, L. M. (2004). El problema del transporte de la caña de azúcar en Cuba. Revista de Investigación Operacional, 25, 148–157.
López, E., Miquel, S., & Plà, L. M. (2006). Sugar cane transportation in Cuba, a case study. European Journal of Operational Research, 174, 374–386.
Martin, F., Pinkney, A., & Yu, X. X. (2001). Cane railway scheduling via constraint logic programming: labelling order and constraints in a real-live application. Annals of Operational Research, 108, 193–209.
Pavia, R., & Morabito, R. (2008). An optimisation model for the aggregate production planning of a Brazilian sugar and ethanol milling company. Annals of Operations Research, 161, 117–130.
Schrage, L. (1997). Optimization modeling with LINDO (5th ed.). New York: Duxbury.
Rizzoli, A. E., Fornara, N., & Gambardella, L. M. (2002). A simulation tool for combined rail/road transport in intermodal terminals. Mathematics and Computers in Simulation, 59, 57–71.
Semenzato, R. (1995). A simulation study of sugar cane harvesting. Agricultural Systems, 47, 427–437.
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Appendix: The mathematical model
Appendix: The mathematical model
where:
- C ijklm =c k ⋅d i,j ::
-
represents the economic coefficients.
- Co i ::
-
represents the opportunity coefficients.
- X ijklm ::
-
are the decision variables.
- c k ::
-
is the specific economic coefficient related to transport k. As it is shown, the way and time in which the cane is cut make no difference because these economic coefficients are just representing transportation costs.
- d ij ::
-
is the distance between origin i and destination j.
- Co i ::
-
opportunity coefficient which represents the preference to cut a field, Co i ≤1.
- TM k ::
-
total transport force of means type k expressed in hours of work
$$ \mathit{CR}_{ijkl} = \frac{D_{ij} \cdot( \frac{1}{Vcc_{k}} + \frac{1}{Vsc_{k}} ) + Tc_{kl}}{Cc_{k}} $$(17)
where:
- D ij ::
-
Distances from origin i to destination j.
- Vcc k ::
-
Speed of the given carriage means k, with load.
- Vsc k ::
-
Speed of the given carriage means k, without load.
- Tc kl ::
-
Waiting time of carriage means k, with cutting system l.
- Cc k ::
-
Loading capacity of carriage means k.
- Cap i :
-
is the production of sugar cane in field i.
- B ilm ∈{0,1}:
-
is the binary variable controlling possible combinations origin-cutting mean per hour.
- Prod l ::
-
production per hour of each l-group of cutting means.
- Y il ∈{0,1}:
-
is the binary variable representing if the cutting mean l has been working or not on field i during the working day.
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López-Milán, E., Plà-Aragonés, L.M. A decision support system to manage the supply chain of sugar cane. Ann Oper Res 219, 285–297 (2014). https://doi.org/10.1007/s10479-013-1361-0
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DOI: https://doi.org/10.1007/s10479-013-1361-0