Abstract
The milk collection problem can be basically defined as the daily collection of raw milk from different points (farms/milk collection centers) and delivering it to a dairy facility. To enhance final dairy quality, it is important to use the appropriate quality of raw milk for each dairy product. However, collecting different types of milk comes with additional logistics costs which significantly increase in an uncertain environment. In this study, we, therefore, propose a novel mathematical model for the collection of different types of milk from producers by multi-tank tankers with split deliveries, uncertain demand, service time and vehicle speed conditions. A real-life case study from a dairy company is solved under different risk assessment scenarios. Indeed, several brand-new benchmark instances for the core problem are presented and solved by utilizing an efficient heuristics approach called enhanced iterative local search. All the case study results show that considering the uncertainty is very critical for designing efficient collection networks. The findings of the study indicate that logistics decision makers should design their collection networks with low, but non-zero, risk levels.
Similar content being viewed by others
References
Basnet C, Foulds LR, Wilson JM (1999) An exact algorithm for a milk tanker scheduling and sequencing problem. Ann Oper Res 86:559–568. https://doi.org/10.1023/A:1018943910798
Beasley JE (1983) Route first—cluster second methods for vehicle routing. Omega 11:403–408. https://doi.org/10.1016/0305-0483(83)90033-6
Brandão J (2016) A deterministic iterated local search algorithm for the vehicle routing problem with backhauls. TOP 24:445–465. https://doi.org/10.1007/s11750-015-0404-x
Butler M, Williams HP, Yarrow L-A (1997) The two-period travelling salesman problem applied to milk collection in Ireland. Comput Optim Appl 7:291–306. https://doi.org/10.1023/A:1008608828763
Butler M, Herlihy P, Keenan PB (2005) Integrating information technology and operational research in the management of milk collection. J Food Eng 70:341–349. https://doi.org/10.1016/j.jfoodeng.2004.02.046
Caceres-Cruz J, Arias P, Guimarans D, Riera D, Juan AA (2014) Rich vehicle routing problem: survey. ACM Comput Surv (CSUR) 47:1–28
Caramia M, Guerriero F (2010) A milk collection problem with incompatibility constraints. Interfaces 40:130–143. https://doi.org/10.1287/inte.1090.0475
Carlsson C, Korhonen P (1986) A parametric approach to fuzzy linear programming. Fuzzy Sets Syst 20:17–30. https://doi.org/10.1016/S0165-0114(86)80028-8
Chen H-K, Hsueh C-F, Chang M-S (2009) Production scheduling and vehicle routing with time windows for perishable food products. Comput Oper Res 36:2311–2319
Chokanat P, Pitakaso R, Sethanan K (2019) Methodology to solve a special case of the vehicle routing problem: a case study in the raw milk transportation system. AgriEngineering 1:75–93
Christofides N, Mingozzi A, Toth P (1979) The vehicle routing problem. In: Christofides N, Mingozzi A, Toth P, Sandi C (eds) Combinatorial optimization, vol 1. Wiley, Chichester, pp 315–338
Claassen G, Hendriks TH (2007) An application of special ordered sets to a periodic milk collection problem. Eur J Oper Res 180:754–769
Cuda R, Guastaroba G, Speranza MG (2015) A survey on two-echelon routing problems. Comput Oper Res 55:185–199. https://doi.org/10.1016/j.cor.2014.06.008
Dantzig G, Fulkerson R, Johnson S (1954) Solution of a large-scale traveling-salesman problem. J Oper Res Soc Am 2:393–410. https://doi.org/10.1287/opre.2.4.393
Endrizzi I et al (2012) The effect of milk collection and storage conditions on the final quality of Trentingrana cheese: sensory and instrumental evaluation. Int Dairy J 23:105–114. https://doi.org/10.1016/j.idairyj.2011.10.004
Fallahi AE, Prins C, Wolfler Calvo R (2008) A memetic algorithm and a tabu search for the multi-compartment vehicle routing problem. Comput Oper Res 35:1725–1741. https://doi.org/10.1016/j.cor.2006.10.006
Frye CP (2013) Regulatory requirements for milk production, transportation and processing. In: Chandan RC (ed) Manufacturing yogurt and fermented milks. Wiley, pp 49–69. https://doi.org/10.1002/9781118481301.ch3
Hoff A, Løkketangen A (2007) A tabu search approach for milk collection in western Norway using trucks and trailers. Proc Sixth Triennial Sympos Transportation Anal(TRISTAN VI), Phuket Island, Thailand
Hsu C-I, Hung S-F, Li H-C (2007) Vehicle routing problem with time-windows for perishable food delivery. J Food Eng 80:465–475
Huang K, Wu K-F, Ardiansyah MN (2019) A stochastic dairy transportation problem considering collection and delivery phases. Transport Res Part E Logist Transport Rev 129:325–338. https://doi.org/10.1016/j.tre.2018.01.018
Jiménez M (1996) Ranking fuzzy numbers through the comparison of its expected intervals. Int J Uncertain Fuzziness Knowl Based Syst 4:379–388
Jiménez M, Arenas M, Bilbao A, Rodrı MV (2007) Linear programming with fuzzy parameters: an interactive method resolution. Eur J Oper Res 177:1599–1609
Jones JB (1953) Economics of milk distribution from farm to dairy. Int J Dairy Technol 6:72–78. https://doi.org/10.1111/j.1471-0307.1953.tb01291.x
Jouzdani J, Sadjadi SJ, Fathian M (2013) Dynamic dairy facility location and supply chain planning under traffic congestion and demand uncertainty: a case study of Tehran. Appl Math Model 37:8467–8483. https://doi.org/10.1016/j.apm.2013.03.059
Lahrichi N, Gabriel Crainic T, Gendreau M, Rei W, Rousseau L-M (2015) Strategic analysis of the dairy transportation problem. J Oper Res Soc 66:44–56. https://doi.org/10.1057/jors.2013.147
Lahyani R, Khemakhem M, Semet F (2015) Rich vehicle routing problems: From a taxonomy to a definition. Eur J Oper Res 241:1–14. https://doi.org/10.1016/j.ejor.2014.07.048
Londoño JC, Tordecilla RD, Martins LdC, Juan AA (2020) A biased-randomized iterated local search for the vehicle routing problem with optional backhauls. TOP. https://doi.org/10.1007/s11750-020-00558-x
Lourenço HR, Martin OC, Stützle T (2003) Iterated local search. In: Glover F, Kochenberger GA (eds) Handbook of metaheuristics. Springer, Boston, pp 320–353. https://doi.org/10.1007/0-306-48056-5_11
Mooney CZ (1997) Monte Carlo simulation, vol 116. Sage Publications
Morais VWC, Mateus GR, Noronha TF (2014) Iterated local search heuristics for the vehicle routing problem with cross-docking. Expert Syst Appl 41:7495–7506. https://doi.org/10.1016/j.eswa.2014.06.010
OECD-FAO (2010) Agricultural Outlook 2010–2019. The Organisation for Economic Co-operation and Development (OECD)—The Food and Agriculture Organization of the United Nations (FAO), Paris, France
OECD-FAO (2019) Agricultural Outlook 2019–2028. The Organisation for Economic Co-operation and Development (OECD)—The Food and Agriculture Organization of the United Nations (FAO), Paris, France
Paredes-Belmar G, Marianov V, Bronfman A, Obreque C, Lüer-Villagra A (2016) A milk collection problem with blending. Transport Res Part E Logist Transport Rev 94:26–43. https://doi.org/10.1016/j.tre.2016.07.006
Paredes-Belmar G, Lüer-Villagra A, Marianov V, Cortés CE, Bronfman A (2017) The milk collection problem with blending and collection points. Comput Electron Agric 134:109–123. https://doi.org/10.1016/j.compag.2017.01.015
Pishvaee MS, Torabi SA (2010) A possibilistic programming approach for closed-loop supply chain network design under uncertainty. Fuzzy Sets Syst 161:2668–2683
Polat O, Topaloğlu D (2019) Milk collection network design in a fuzzy environment. In: Paper presented at the 18th international conference on economy & business, burgas, Bulgaria, 20–24 August 2019
Polat O, Kalayci CB, Kulak O, Günther H-O (2015) A perturbation based variable neighborhood search heuristic for solving the vehicle routing problem with simultaneous pickup and delivery with time limit. Eur J Oper Res 242:369–382. https://doi.org/10.1016/j.ejor.2014.10.010
Polat O, Capraz O, Gungor A (2018) Modelling of WEEE recycling operation planning under uncertainty. J Clean Prod 180:769–779. https://doi.org/10.1016/j.jclepro.2018.01.187
Prins C (2004) A simple and effective evolutionary algorithm for the vehicle routing problem. Comput Oper Res 31:1985–2002. https://doi.org/10.1016/S0305-0548(03)00158-8
Prodhon C, Prins C (2014) A survey of recent research on location-routing problems. Eur J Oper Res 238:1–17. https://doi.org/10.1016/j.ejor.2014.01.005
Reed M, Yiannakou A, Evering R (2014) An ant colony algorithm for the multi-compartment vehicle routing problem. Appl Soft Comput 15:169–176. https://doi.org/10.1016/j.asoc.2013.10.017
Sankaran JK, Ubgade RR (1994) Routing tankers for dairy milk pickup. Interfaces 24:59–66. https://doi.org/10.1287/inte.24.5.59
Sethanan K, Pitakaso R (2016) Differential evolution algorithms for scheduling raw milk transportation. Comput Electron Agric 121:245–259. https://doi.org/10.1016/j.compag.2015.12.021
Silvestrin PV, Ritt M (2017) An iterated tabu search for the multi-compartment vehicle routing problem. Comput Oper Res 81:192–202. https://doi.org/10.1016/j.cor.2016.12.023
Subramanian A, dos Anjos Formiga Cabral L (2008) An ILS based heuristic for the vehicle routing problem with simultaneous pickup and delivery and time limit. In: van Hemert J, Cotta C (eds) Evolutionary computation in combinatorial optimization. Springer, Berlin, pp 135–146. https://doi.org/10.1007/978-3-540-78604-7_12
Subramanian A, Penna PHV, Uchoa E, Ochi LS (2012) A hybrid algorithm for the heterogeneous fleet vehicle routing problem. Eur J Oper Res 221:285–295. https://doi.org/10.1016/j.ejor.2012.03.016
Subramanian A, Uchoa E, Ochi LS (2013) A hybrid algorithm for a class of vehicle routing problems. Comput Oper Res 40:2519–2531. https://doi.org/10.1016/j.cor.2013.01.013
Tarantilis C, Kiranoudis C (2001) A meta-heuristic algorithm for the efficient distribution of perishable foods. J Food Eng 50:1–9
UN (2019) World Population Prospects 2019 Highlights vol ST/ESA/SER.A/423. United Nations (UN), Department of Economic and Social Affairs Population Division, New Yourk, USA
Wang X, Shao S, Tang J (2020) Iterative local-search heuristic for weighted vehicle routing problem. IEEE Trans Intell Transport Syst. https://doi.org/10.1109/TITS.2020.2983398
Acknowledgements
This work supported by the Scientific and Technological Research Council of Turkey (TÜBİTAK) under 217M578 project. This support is gratefully acknowledged.
Author information
Authors and Affiliations
Corresponding author
Additional information
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Rights and permissions
About this article
Cite this article
Polat, O., Topaloğlu, D. Collection of different types of milk with multi-tank tankers under uncertainty: a real case study. TOP 30, 1–33 (2022). https://doi.org/10.1007/s11750-021-00598-x
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s11750-021-00598-x
Keywords
- Milk collection problem
- Multi-compartment vehicle routing problem
- Fuzzy optimization
- Iterative local search
- Dairy logistics