Mixed integer linear programming approaches for solving the raw material allocation, routing and scheduling problems in the forest industry

Bordón, M.; Montagna, J.; Corsano, C.

Growing Science » International Journal of Industrial Engineering Computations » Mixed integer linear programming approaches for solving the raw material allocation, routing and scheduling problems in the forest industry

Journals

IJIEC Volumes

Volume 1 (17)
- Issue 1 (9)
- Issue 2 (8)

Volume 2 (68)
- Issue 1 (12)
- Issue 2 (20)
- Issue 3 (20)
- Issue 4 (16)

Volume 3 (76)
- Issue 1 (9)
- Issue 2 (15)
- Issue 3 (20)
- Issue 4 (12)
- Issue 5 (20)

Volume 4 (50)
- Issue 1 (14)
- Issue 2 (10)
- Issue 3 (12)
- Issue 4 (14)

Volume 5 (47)
- Issue 1 (13)
- Issue 2 (12)
- Issue 3 (12)
- Issue 4 (10)

Volume 6 (39)
- Issue 1 (7)
- Issue 2 (12)
- Issue 3 (10)
- Issue 4 (10)

Volume 7 (47)
- Issue 1 (10)
- Issue 2 (14)
- Issue 3 (10)
- Issue 4 (13)

Volume 8 (30)
- Issue 1 (9)
- Issue 2 (7)
- Issue 3 (8)
- Issue 4 (6)

Volume 9 (32)
- Issue 1 (9)
- Issue 2 (6)
- Issue 3 (7)
- Issue 4 (10)

Volume 10 (34)
- Issue 1 (8)
- Issue 2 (10)
- Issue 3 (8)
- Issue 4 (8)

Volume 11 (36)
- Issue 1 (9)
- Issue 2 (8)
- Issue 3 (9)
- Issue 4 (10)

Volume 12 (29)
- Issue 1 (9)
- Issue 2 (6)
- Issue 3 (8)
- Issue 4 (6)

Volume 13 (41)
- Issue 1 (10)
- Issue 2 (8)
- Issue 3 (10)
- Issue 4 (13)

Volume 14 (50)
- Issue 1 (11)
- Issue 2 (15)
- Issue 3 (9)
- Issue 4 (15)

Volume 15 (55)
- Issue 1 (19)
- Issue 2 (15)
- Issue 3 (12)
- Issue 4 (9)

Volume 16 (12)
- Issue 1 (12)

Keywords

Authors

Countries

International Journal of Industrial Engineering Computations

ISSN 1923-2934 (Online) - ISSN 1923-2926 (Print) Quarterly Publication Volume 11 Issue 4 pp. 525-548 , 2020

Mixed integer linear programming approaches for solving the raw material allocation, routing and scheduling problems in the forest industry Pages 525-548 Download PDF

Authors: Maximiliano R. Bordón, Jorge M. Montagna, Corsano Corsano

DOI: 10.5267/j.ijiec.2020.5.001

Keywords: Log transportation, Vehicle routing, Scheduling, MILP, Forest industry

Abstract: Transportation planning in forest industry is a challenging activity since it involves complex decisions about raw material allocation, vehicle routing and scheduling of trucks arrivals to both harvest areas and the plants. In the Argentine context, specifically in the Argentinean Northeast (NEA) region, the forest industry plays essential role for the economic development and, among the included activities, the transportation is the key element considering the volumes that must be moved and the distances to be traveled. Therefore, enhancing efficiency in the transportation activity improves significantly the performance of this industry. In this work, a Mixed Integer Linear Programming (MILP) model is presented, where raw material allocation, vehicle routing and scheduling of trucks arrivals are simultaneously addressed. Since the resolution times of the proposed integrated MILP model are prohibitive for large instances, a hierarchical approach is also presented. The considered decomposition approach involves two stages: in the first phase, the raw material allocation and vehicle routing problems are solved through a MILP model, while in the second phase, fixing the route for each truck according to the results of the previous step, the scheduling of truck arrivals to both the harvest areas and the plants is solved through a new MILP model. The obtained results show that the proposed approach is very effective and could be easily applied in this industry.

How to cite this paper

 Bordón, M., Montagna, J & Corsano, C. (2020). Mixed integer linear programming approaches for solving the raw material allocation, routing and scheduling problems in the forest industry.International Journal of Industrial Engineering Computations , 11(4), 525-548.

Refrences

Audy, J. F., El Hachemi, N., Michel, L., & Rousseau, L. M. (2011). Solving a combined routing and scheduling problem in forestry. In International Conference on Industrial Engineering and Systems Management, May (pp. 25-27).
Audy, J. F., D'Amours, S., & Rönnqvist, M. (2012). Planning methods and decision support systems in vehicle routing problems for timber transportation: a review (Vol. 45). Montreal, Canada: CIRRELT.
Bordón, M. R., Montagna, J. M., & Corsano, G. (2018). An exact mathematical formulation for the optimal log transportation. Forest Policy and Economics, 95, 115-122.
Borges, J. G., Diaz-Balteiro, L., McDill, M. E., & Rodriguez, L. C. (2014). Management of Industrial Forest Plantations. Springer.
Broz, D. R., Rossit, D. A., Rossit, D. G., & Cavallin, A. (2018). The Argentinian forest sector: opportunities and challenges in supply chain management. Uncertain Supply Chain Management, 6(4), 375-392.
Contreras, M. A., Chung, W., & Jones, G. (2008). Applying ant colony optimization metaheuristic to solve forest transportation planning problems with side constraints. Canadian Journal of Forest Research, 38(11), 2896-2910.
D’Amours, S., Rönnqvist, M. & Weintraub, A. (2008). Using operational research for supply chain planning in the forest products industry. INFOR, 46(4), 265–281.
Derigs, U., Pullmann, M., Vogel, U., Oberscheider, M., Gronalt, M., & Hirsch, P. (2012). Multilevel neighborhood search for solving full truckload routing problems arising in timber transportation. Electronic Notes in Discrete Mathematics, 39, 281-288.
El Hachemi, N., Gendreau, M., & Rousseau, L. M. (2011). A hybrid constraint programming approach to the log-truck scheduling problem. Annals of Operations Research, 184(1), 163-178.
El Hachemi, N., Gendreau, M., & Rousseau, L. M. (2013). A heuristic to solve the synchronized log-truck scheduling problem. Computers & Operations Research, 40(3), 666-673.
El Hachemi, N., El Hallaoui, I., Gendreau, M., & Rousseau, L. M. (2014). Flow-based integer linear programs to solve the weekly log-truck scheduling problem. Annals of Operations Research, 232(1), 87-97.
Flisberg, P., Lidén, B., & Rönnqvist, M. (2009). A hybrid method based on linear programming and tabu search for routing of logging trucks. Computers & Operations Research, 36(4), 1122-1144.
Gronalt, M., & Hirsch, P. (2007). Log-truck scheduling with a tabu search strategy. In Metaheuristics (65-88). Springer, Boston, MA.
Haridass, K., Valenzuela, J., Yucekaya, A. D., & McDonald, T. (2014). Scheduling a log transport system using simulated annealing. Information Sciences, 264, 302-316.
Lin, P., Contreras, M. A., Dai, R., & Zhang, J. (2016). A multilevel ACO approach for solving forest transportation planning problems with environmental constraints. Swarm and Evolutionary Computation, 28, 78-87.
Rosenthal, R.E. (2017). GAMS – A user’s guide. GAMS development corporation. Washington, DC.