VEHICLE SCHEDULING IN A HARVEST SEASON
DOI:
https://doi.org/10.5937/ekoPolj1802633GKeywords:
vehicle scheduling, harvesting process, sugar beet collectionAbstract
The collection of agricultural goods is a very dynamic process which involves the coordination of hundreds of transport routes and machines with respect the processing capacities at a factory. Numerous fluctuations in the number of transport vehicles, malfunctioning on engaged machines and weather conditions make the process of planning and maximizing the utilization of all resources very diffcult. In this paper we present a mathematical model and a heuristic algorithm that in a short period of time fnds nearly optimal solutions, which enables a dispatcher to re-plan and update the collection plan according to new constraints.
Downloads
Download data is not yet available.
References
1. Ali, O., Verlinden, B. and Van Oudheusden, D. (2009) Infeld logistics planning for crop-harvesting operations, Engineering Optimization, vol. 41, n. 2 https://doi.org/10.1080/03052150802406540
2. Bala, K., Brcanov, D. and Gvozdenović, N., (2017) Two-echelon location routing synchronized with production schedules and time windows, Central European Journal of Operations Research vol. 25, n. 3, p. 525-543.
3. Černý, V., (1985) Thermodynamical approach to the traveling salesman problem: An effcient simulation algorithm, Journal of Optimization Theory and Applications vol. 45, p. 41–51.
4. Fazekaš, T., Bobera, D., Ćirić, Z. (2017) Ecologically and Economiccaly Sustainable
5. Agricultural Transportation Based on Advanced Information Technologies, Journal Economics of Agriculture, Vol. 64 (2) p. 405-860.
6. Fishpool, P., Maximising the effciency of the UK Sugar Beet supply chain (2016) A Nuffeld (UK) Farming Scholarships Trust Report, http://nuffeldinternational.org/live/Report/UK/2015/paul-fshpool.
7. Gebresenbet, G. and Ljungberg, D., (2001) IT—Information Technology and the Human Interface, Journal of Agricultural Engineering Research, vol. 80 n. 4, p. 329-342.
8. Kirkpatrick, S., Gelatt Jr, C. D. and Vecchi, M. P. (1983) Optimization by Simulated Annealing, Science vol. 220 p. 671–680. doi:10.1126/science.220.4598.671
9. Kontić, Lj., Vukasović, D., The Impact of Grains Transportation Revenues on Total Revenue: The Case of Serbia, Journal Economics of Agriculture (2017) Vol. 64, (2) p. 483-495.
10. Lamsal, K., Jones, P.C., Thomas, B.W., Harvest logistics in agricultural systems with multiple, independent producers and no on-farm storage, Computers & Industrial Engineering (2016) Vol. 91, 129-138
11. López-Milán, E. & Plà-Aragonés, L.M., A decision support system to manage the supply chain of sugar cane, Annals of Operations Research (2014) Vol. 219 (1) 285-297. https://doi.org/10.1007/s10479-013-1361-0
12. Sedlak, O., Jovin, S., Pejanović, R., Ćirić, Z., Eremić Đođić, J. (2016) Access to Finance for Micro, Small, and Medium Business Units in Serbian Agribusiness, Journal Economics of Agriculture (2016) Vol. 63, (4) p. 1113-1484.
13. Steinzen, I., Gintner, V., Suhl, L. and Kliewer, N., (2010) A time-space network approach for the integrated vehicle and crew-scheduling problem with multiple depots, Transportation Science vol.44, p. 367–382.
2. Bala, K., Brcanov, D. and Gvozdenović, N., (2017) Two-echelon location routing synchronized with production schedules and time windows, Central European Journal of Operations Research vol. 25, n. 3, p. 525-543.
3. Černý, V., (1985) Thermodynamical approach to the traveling salesman problem: An effcient simulation algorithm, Journal of Optimization Theory and Applications vol. 45, p. 41–51.
4. Fazekaš, T., Bobera, D., Ćirić, Z. (2017) Ecologically and Economiccaly Sustainable
5. Agricultural Transportation Based on Advanced Information Technologies, Journal Economics of Agriculture, Vol. 64 (2) p. 405-860.
6. Fishpool, P., Maximising the effciency of the UK Sugar Beet supply chain (2016) A Nuffeld (UK) Farming Scholarships Trust Report, http://nuffeldinternational.org/live/Report/UK/2015/paul-fshpool.
7. Gebresenbet, G. and Ljungberg, D., (2001) IT—Information Technology and the Human Interface, Journal of Agricultural Engineering Research, vol. 80 n. 4, p. 329-342.
8. Kirkpatrick, S., Gelatt Jr, C. D. and Vecchi, M. P. (1983) Optimization by Simulated Annealing, Science vol. 220 p. 671–680. doi:10.1126/science.220.4598.671
9. Kontić, Lj., Vukasović, D., The Impact of Grains Transportation Revenues on Total Revenue: The Case of Serbia, Journal Economics of Agriculture (2017) Vol. 64, (2) p. 483-495.
10. Lamsal, K., Jones, P.C., Thomas, B.W., Harvest logistics in agricultural systems with multiple, independent producers and no on-farm storage, Computers & Industrial Engineering (2016) Vol. 91, 129-138
11. López-Milán, E. & Plà-Aragonés, L.M., A decision support system to manage the supply chain of sugar cane, Annals of Operations Research (2014) Vol. 219 (1) 285-297. https://doi.org/10.1007/s10479-013-1361-0
12. Sedlak, O., Jovin, S., Pejanović, R., Ćirić, Z., Eremić Đođić, J. (2016) Access to Finance for Micro, Small, and Medium Business Units in Serbian Agribusiness, Journal Economics of Agriculture (2016) Vol. 63, (4) p. 1113-1484.
13. Steinzen, I., Gintner, V., Suhl, L. and Kliewer, N., (2010) A time-space network approach for the integrated vehicle and crew-scheduling problem with multiple depots, Transportation Science vol.44, p. 367–382.
Downloads
Published
2018-06-27
How to Cite
Gvozdenović, N., & Brcanov, D. (2018). VEHICLE SCHEDULING IN A HARVEST SEASON. Ekonomika Poljoprivrede, 65(2), 633–642. https://doi.org/10.5937/ekoPolj1802633G
Issue
Section
Original scientific papers
