Planning methods and decision support systems in vehicle routing problems for timber transportation: a review

References

• Acuna M, Ghaffariyan MR, Brown M, 2010. Analysis of factors that affect the transport efficiency of in-field chipping operations. Report in Harvesting and Operations, CRC for Forestry, Bulletin 11, pp. 1–4.
   Google Scholar
• Acuna M, Brown M, Mirowski L, 2011. Improving forestry transport efficiency through truck schedule optimization: a case study and software tool for the Australian industry. Austro 2011 & FORMEC 2011; Oct 9-12; Graz and Rein (Austria).
   Google Scholar
• Amrouss A, Gendreau M, Gendron B. 2016. Managing unforeseen events in forest transportation. J Sci Techn for Produ Proce. 5(5):40–50.
   Google Scholar
• Amrouss A, El Hachemi N, Gendreau M, Gendron B. 2017. Real-time management of transportation disruptions in forestry. Comput Oper Res. 83:95–105. doi:10.1016/j.cor.2017.02.008.
   Web of Science ®Google Scholar
• Andersson G, Flisberg P, Lidén B, Rönnqvist M. 2008. RuttOpt: a decision support system for routing of logging trucks. Canadian J For Res. 38(7):1784–1796.
   Google Scholar
• Andersson G. 2012. Forestry research institute of Sweden, personal communication. March and June.
   Google Scholar
• Audy J-F, D’Amours S, Rousseau L-M, Favreau J, Marier P, 2007. Virtual transportation manager: a web-based system for transportation optimization in a network of business units. In: 3rd Forest Engineering Conference, October 1-4, Canada: Mont-Tremblant.
   Google Scholar
• Audy J-F, El Hachemi N, Michel L, Rousseau L-M, 2011a. Solving a combined routing and scheduling problem in forestry. International Conference on Industrial Engineering and Systems Management; May 25-27, Metz, France.
   Google Scholar
• Audy J-F, Lidén B, Favreau J, 2011b. Issues and solutions for implementing operational decision support system – an application in timber truck routing system. In: Ackerman P, Ham H, Gleasure E, (Eds.). 4th Forest Engineering Conference, April 5-7, White River, South Africa. Stellenbosch University, p. 94–97.
   Google Scholar
• Audy J-F, D’Amours S, Rönnqvist M. 2012a. An empirical study on coalition formation and cost/savings allocation. Int J Prod Econ. 136(1):13–27. doi:10.1016/j.ijpe.2011.08.027.
   Web of Science ®Google Scholar
• Audy J-F, Pinotti M, Westlund K, D’Amours S, LeBel L, Rönnqvist M. 2012b. Alternative logistic concepts fitting different wood supply situations and markets. CIRRELT Research Document 2012-24. Canada: CIRRELT; p. 348.
   Google Scholar
• Audy J-F, D’Amours S, Rousseau L-M, Favreau J. 2013. Virtual transportation manager: a decision support system for collaborative forest transportation. CIRRELT Research Document 2013-34. Canada: CIRRELT. p. 57.
   Google Scholar
• Azouzi R, D’Amours S. 2016. Framework for information and knowledge sharing in collaborative modeling of the forest products value chain. In: D’Amours S, Ouhimmou M, Audy JF, Feng Y, editors. Forest value chain optimization and sustainability. New York: CRC Press, Taylor & Francis Group; p. 183–206.
   Google Scholar
• Basso F, D’Amours S, Rönnqvist M, Weintraub A. 2019. A survey on obstacles and difficulties of practical implementation of horizontal collaboration in logistics. Int Trans Oper Res. 26(3):775–793. doi:10.1111/itor.12577.
   Web of Science ®Google Scholar
• Berbeglia G, Cordeau J-F, Gribkovskaia I, Laporte G. 2007. Static pickup and delivery problems: a classification scheme and survey. TOP. 15(1):1–31. doi:10.1007/s11750-007-0009-0.
   Web of Science ®Google Scholar
• Berbeglia G, Cordeau J-F, Laporte G. 2010. Dynamic pickup and delivery problems. Eur J Oper Res. 202(1):8–15. doi:10.1016/j.ejor.2009.04.024.
   Web of Science ®Google Scholar
• Bordòn MR, Montagna JM, Corsano G. 2018. An exact mathematical formulation for the optimal log transportation. For Policy Econ. 95:115–122. doi:10.1016/j.forpol.2018.07.017.
   Web of Science ®Google Scholar
• Bordòn MR, Montagna JM, Corsano G. 2020. Mixed integer linear programming approaches for solving the raw material allocation, routing and scheduling problems in the forest industry. Int J Ind Eng Comput. 11(4):525–548. doi:10.5267/j.ijiec.2020.5.001.
   Web of Science ®Google Scholar
• Bordòn MR, Montagna JM, Corsano G. 2021. Solution approaches for solving the log transportation problem. Appl Math Model. 98:611–627. doi:10.1016/j.apm.2021.06.003.
   Web of Science ®Google Scholar
• Boutin F 2012 . FPInnovations, personal communication.
   Google Scholar
• Brown M, Michaelsen J, Hickman A, Provencher Y. 2003. Potential for multi-use trailers in the Canadian forest industry. CR-0196-1. Canada: Forest Engineering Research Institute of Canada.
   Google Scholar
• Brown MW. 2012. University of the sunshine coast and CRC for forestry, personal communication. March.
   Google Scholar
• Carlsson D, D’Amours S, Martel A, Rönnqvist M. 2008. Decisions and methodology for planning the wood fiber flow in the forest supply chain. In: Koster R, Delfmann W, editors. Recent developments in supply chain management. Finland: Helsinki University Press; p. 11–39.
   Google Scholar
• Clarke G, Wright JR. 1964. Scheduling of vehicles from a central depot to a number of delivery points. Oper Res. 12(4):568–581. doi:10.1287/opre.12.4.568.
   Web of Science ®Google Scholar
• Chen C, Gan J, Zhang Z, Qiu R. 2020. Multi-objective and multi-period optimization of a regional timber supply network with uncertainty. Canadian J For Res. 50(2):203–214. doi:10.1139/cjfr-2018-0551.
   Google Scholar
• Cordeau J-F, Laporte G, Mercier A. 2001. A unified tabu search heuristic for vehicle routing problems with time windows. J Oper Res Soc. 52(8):928–936. doi:10.1057/palgrave.jors.2601163.
   Web of Science ®Google Scholar
• Cordeau J-F, Laporte G, Potvin J-Y, Savelsbergh MWP. 2007. Transportation on demand. In: Barnhart C, Laporte G, editors. Transportation, handbooks in operations research and management science. Vol. 14, Chapter 7. Amsterdam: North-Holland; p. 429–466.
   Google Scholar
• Dantzig GB, Ramser JH. 1959. The truck dispatching problem. Manage Sci. 6(1):80–91. doi:10.1287/mnsc.6.1.80.
   Web of Science ®Google Scholar
• D’Amours S, Rönnqvist M, Weintraub A. 2008. Using operational research for supply chain planning in the forest products industry. INFOR: Inf Syst Oper Res. 46(4):265–281. doi:10.3138/infor.46.4.265.
   Web of Science ®Google Scholar
• D’Amours S, Azouzi R, Audy J-F, Marier P, Sarrazin F, 2013. Extension and usage explorations of a decision support system for collaborative planning of log trucks. In: 15th Symposium for Systems Analysis in Forest Resources; Aug 19-21, Quebec City, Canada.
   Google Scholar
• 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. Electron Notes Discrete Math. 39:281–288. doi:10.1016/j.endm.2012.10.037.
   Google Scholar
• Dorval JS, Lehoux N, Gaudreault J, Marier P, 2012. Collaboration in transportation management – case study for the forest industry. In: 4th International Conference on Information Systems, Logistics and Supply Chain; Aug 26-29, Quebec City, Canada.
   Google Scholar
• El Hachemi N, Gendreau M, Rousseau L-M, 2008. Solving a log-truck scheduling problem with constraint programming. In: Perron L, Trick MA, (Eds.). 5th International Conference on Integration of AI and OR Techniques in Constraint Programming for Combinatorial Optimization Problems, Lecture Notes in Computer Science Paris, France, Vol. 5015; Springer. p. 293–297.
   Google Scholar
• El Hachemi N, Gendreau M, Rousseau L-M, 2009. A heuristic to solve the weekly log-truck scheduling problem. In: International Conference on Industrial Engineering and Systems Management; May 13-15, Montreal, Canada.
   Google Scholar
• El Hachemi N, Gendreau M, Rousseau L-M. 2011. A hybrid constraint programming approach to the log-truck scheduling problem. Annals Oper Res. 184(1):163–178. doi:10.1007/s10479-010-0698-x.
   Web of Science ®Google Scholar
• El Hachemi N, Gendreau M, Rousseau L-M. 2013. A heuristic to solve the synchronized log-truck scheduling problem. Comput Oper Res. 40(3):666–673. doi:10.1016/j.cor.2011.02.002.
   Web of Science ®Google Scholar
• 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 Oper Res. doi:10.1007/s10479-014-1527-4
   PubMed Web of Science ®Google Scholar
• Emeyriat R, Bigot M. 2006. Management of wood haulage through GIS/GPS tools in maritime pine forest (France). In: Ackerman PA, Längin DW, Antonides MC, editors. International precision forestry symposium; Mar 5-10; Stellenbosch (South Africa. Stellenbosch): Stellenbosch University; p. 331–340.
   Google Scholar
• Epstein R, Morales R, Serón J, Weintraub A. 1999. Use of OR systems in the chilean forest industries. Interfaces. 29(1):7–29. doi:10.1287/inte.29.1.7.
   Web of Science ®Google Scholar
• Epstein R, Karlsson J, Rönnqvist M, Weintraub A. 2007. Forest transportation. In: Weintraub A, Romero C, Bjorndal T, Epstein R, editors. Handbook of operations research in natural resources, international series in operations research and management science. Vol. 99, Chapter 20. New York: Kluwer Academic Publishers; p. 391–403.
   Google Scholar
• Eriksson J, Rönnqvist M, 2003. Transportation and route planning: Åkarweb - a web-based planning system. In: Iwarsson Wide M, Hallberg I, (Eds.). 2nd Forest Engineering Conference; May 12-15; Växjö, Sweden. Uppsala: SkogForsk. p. 48–57.
   Google Scholar
• Feng Y, Audy J-F. 2020. Forestry 4.0: a framework for the forest supply chain toward Industry 4.0. Gestão & Produção. 27(4):1–21. doi:10.1590/0104-530x5677-20.
   Google Scholar
• Fjled D. 2014. Swedish university of agricultural sciences, personal communication. Aug.
   Google Scholar
• Flisberg P, Lidén B, Rönnqvist M. 2009. A hybrid method based on linear programming and tabu search for routing of logging trucks. Comput Oper Res. 36(4):1122–1144. doi:10.1016/j.cor.2007.12.012.
   Web of Science ®Google Scholar
• Flisberg P, Frisk M, Rönnqvist M. 2012a. FuelOpt: a decision support system for forest fuel logistics. J Oper Res Soc. 163(11):1600–1612. doi:10.1057/jors.2011.157.
   Google Scholar
• Flisberg P, Lidén B, Rönnqvist M, Selander J. 2012b. Route selection for best distances in road databases based on drivers’ and customers’ preferences. Canadian J For Res. 42(6):1126–1140. doi:10.1139/x2012-063.
   Google Scholar
• Forsberg M, Frisk M, Rönnqvist M. 2005. FlowOpt: a decision support tool for strategic and tactical transportation planning in forestry. Int J For Eng. 16(2):101–114. doi:10.1080/14942119.2005.10702519.
   Google Scholar
• Frisk M, Jörnsten K, Göthe-Lundgren M, Rönnqvist M. 2010. Cost allocation in collaborative forest transportation. Eur J Oper Res. 205(2):448–458. doi:10.1016/j.ejor.2010.01.015.
   Web of Science ®Google Scholar
• Frisk M. 2012. Forestry Research Institute of Sweden, personal communication. Mar-Apr.
   Google Scholar
• Gerasimov Y, Sokolov A, Karjalainen T. 2008. GIS-based decision-support program for planning and analyzing short-wood transport in Russia. Croatian J For Eng. 29(2):163–176.
   Web of Science ®Google Scholar
• Gerasimov Y, Sokolov A, Fjeld D. 2013. Improving cut-to-length operations management in Russian logging companies using a new decision support system. Baltic Forestry. 19(1):89–105.
   Web of Science ®Google Scholar
• Gerasimov Y, Sokolov A. 2014. Decision making toolset for woody biomass supply chain in Karelia. Appl Mech Mater. 459:319–324. www.scientific.net/AMM.459.319.
   Google Scholar
• Gendreau M, El Hachemi N, Rousseau L-M, 2009. A hybrid LS/CP approach to solve the weekly log-truck scheduling problem. 8th Metaheuristics International Conference; Jul 13-16; Hamburg, Germany.
   Google Scholar
• Gingras C, Cordeau J-F, Laporte G. 2007. Un algorithme de minimisation du transport à vide appliqué à l’industrie forestière [An algorithm for minimizing unloaded transportation applied to the forest industry]. INFOR: Inf Syst Oper Res. 45(1):41–47. doi:10.3138/infor.45.1.41.
   Google Scholar
• Gingras J-F, Charette F. 2017. FPInnovations’ forestry 4.0 initiative. FPInnovations, Canada. [Accessed 2019 Jul 23]. http://blog.fpinnovations.ca/blog/2017/06/20/forestry-4-0-featured-as-part-of-cif-ifc-e-lecture-series/
   Google Scholar
• Greene D. 2012. University of georgia, personal communication. Mar-Jun.
   Google Scholar
• Gronalt M, Hirsch P. 2007. Log-truck scheduling with a tabu search strategy. In: Doerner KF, Gendreau M, Greistorfer P, Gutjahr WJ, Hartl RF, Reimann M, editors. Metaheuristics - progress in complex systems optimization. New York: Springer; p. 65–88.
   Google Scholar
• Han S-K, Murphy GE. 2012. Solving a woody biomass truck scheduling problem for a transport company in Western Oregon, USA. Biomass Bioenergy. 44:47–55. doi:10.1016/j.biombioe.2012.04.015.
   Web of Science ®Google Scholar
• Haridass K, Valenzuela J, Yucekaya AD, McDonald T. 2014. Scheduling a log transport system using simulated annealing. Inf Sci (Ny). 264:302–316. doi:10.1016/j.ins.2013.12.005.
   Web of Science ®Google Scholar
• Hirsch P. 2011. Minimizing empty truck loads in round timber transport with tabu search strategies. Int J Inf Syst Supply Chain Manage. 4(2):15–41. doi:10.4018/jisscm.2011040102.
   Google Scholar
• Hirsch P. 2012 June. University of natural resources and life sciences. Personnal communication.
   Google Scholar
• Hirsch P, Gronalt M. 2013. The timber transport order smoothing problem as part of the three-stage planning approach for round timber transport. J Appl Oper Res. 5(2):70–81.
   Google Scholar
• Jacqmin F 2012. Trimble Forestry Automation, personal communication. February and March.
   Google Scholar
• Kent E, Atkin JAD, Qu R. 2014. Vehicle routing in a forestry commissioning operation using ant colony optimisation. In Dediu AH, Lozano M, Martin-Vide C, editors. Theory and practice of natural computing. Vol. 8890, TPNC 2014. Lecture Notes in Computer Science. Cham: Springer; p. 95–106.
   Google Scholar
• Kogler C, Rauch P. 2019. A discrete-event simulation model to test multimodal strategies for a greener and more resilient wood supply chain. Canadian J For Res. 49(10):1298–1310. doi:10.1139/cjfr-2018-0542.
   Google Scholar
• Kokenge KS, 2011. Opportunities and challenges for decision support systems in log truck scheduling and dispatching. Master thesis, Oregon State University, U.S.
   Google Scholar
• Laqidi I, Audy J-F, Forget P, Leclerc M. 2017. Méthodologie d’évaluation et de suivi de la performance en transport routier collaboratif. In: 12e Congrès International de Génie Industriel Compiègne, France; May 3-5; Compiègne (France): Université de Technologie de Compiègne; p. 1–11.
   Google Scholar
• Lepage D. 2012 March. FPInnovations, personal communication.
   Google Scholar
• Lidén B. 2011 December. Forestry Research Institute of Sweden, personal communication.
   Google Scholar
• Linnainmaa S, Savola J, Jokinen O, 1995. EPO: a knowledge based system for wood procurement management. In: Aikins J, M Shrobe H, (Eds.). 7th Conference on Innovative Applications of Artificial Intelligence; Aug 20-23; Montreal, Canada. Menlo Park: AAAI Press. p. 107–113.
   Google Scholar
• Ludbrook M. 2011 August. Asset forestry logistics, personal communication.
   Google Scholar
• Malladi KT, Sowlati T. 2017. Optimization of operational level transportation planning in forestry: a review. Int J For Eng. 28(3):198–210. doi:10.1080/14942119.2017.1362825.
   Web of Science ®Google Scholar
• Marier P, Audy J-F, Gingras C, D’Amours S, 2007. Collaborative wood transportation with the virtual transportation manager. In: Blanchet P, (Eds.), International Scientific Conference on Hardwood Processing; Sept 24-26; Quebec City, Canada. Quebec: FPInnovations-Forintek. p. 191–198.
   Google Scholar
• Marques A, Pinho de Sousa J, Rönnqvist M, Jafe R. 2014. Combining optimization and simulation tools for short-term planning and analysis in forest operations. Scand J For Res. 29(1):166–177. doi:10.1080/02827581.2013.856937.
   Google Scholar
• Marques AF, Rönnqvist M, D’Amours S, Weintraub A, Gonçalves J, Borges JG, Flisberg P. 2012. Solving the raw materials reception problem using revenue management principles: an application to a Portuguese pulp mill. CIRRELT Research Document 2012-29. Canada: CIRRELT. p. 27.
   Google Scholar
• Marshall H. 2007. Log merchandizing model used in mechanical harvesting. In: Weintraub A, Romero C, Bjorndal T, Epstein R, editors. Handbook of Operations Research in Natural Resources, International Series in Operations Research and Management Science. New York: Kluwer Academic Publishers; p. 379–389.
   Google Scholar
• McCary J, 2009. Coaching strategies – an always-thinking contractor teams up with his wood source to boost efficiency and profitability. Southern Loggin’ Times. Aug.
   Google Scholar
• McDonald T, Taylor S, Rummer RB, Valenzuela J. 2001a. Information needs for increasing log transport efficiency. In: 1st international precision forestry cooperative symposium; Jun 17-20; Seattle (United-States. Seattle): College of Forest Resources; p. 181–184.
   Google Scholar
• McDonald T, Taylor S, Valenzuela J. 2001b. Potential for shared log transport services. In: Wang J, Wolford M, McNeel J, editors. 24th annual COFE meeting; Jul 15-19; Snowshoe (United-States. Corvallis): Council on Forest Engineering; p. 115–120
   Google Scholar
• McDonald T, Haridass K, Valenzuela J, 2010. Mileage savings from optimization of coordinated trucking. In: 33rd Annual COFE Meeting; Jun 6-9; Auburn, USA.
   Google Scholar
• Melchiori L, Nasini G, Montagna JM, Corsano G. 2022. A mathematical modeling for simultaneous routing and scheduling of logging trucks in the forest supply chain. For Policy Econ. 136:102693. doi:10.1016/j.forpol.2022.102693.
   Web of Science ®Google Scholar
• Mendell BC, Haber JA, Sydor T. 2006. Evaluating the potential for shared log truck resources in middle Georgia. South J Appl For. 30(2):86–91. doi:10.1093/sjaf/30.2.86.
   Google Scholar
• Michaelsen J. 2012. FPInnovations, personal communication. March, April and June.
   Google Scholar
• Mirowski L, Ghaffariyan MR, Wise A, Acuna M, Turner P, 2016. Reducing transport costs through optimised transport planning: a case study using the FastTRUCK software tool. Australasian Conference on Information Systems; Wollongong.
   Google Scholar
• Monti CA, Gomide LR, Oliveira RM, França LC. 2020. Optimization of wood supply: the forestry routing optimization model. Anais da Academia Brasileira de Ciências. 92(3). doi:10.1590/0001-3765202020200263.
   PubMed Web of Science ®Google Scholar
• Murphy G. 2003. Reducing trucks on the road through optimal route scheduling and shared log transport services. South J Appl For. 27(3):198–205. doi:10.1093/sjaf/27.3.198.
   Web of Science ®Google Scholar
• Oberscheider M, Zazgornik J, Henriksen CB, Gronalt M, Hirsch P. 2013. Minimizing driving times and greenhouse gas emissions in timber transport with a near-exact solution approach. Scand J For Res. 28(5):493–506. doi:10.1080/02827581.2012.758309.
   Web of Science ®Google Scholar
• Palmgren M, Rönnqvist M, Värbrand P. 2003. A solution approach for log truck scheduling based on composite pricing and branch and bound. Int Tran Oper Res. 10(5):433–447. doi:10.1111/1475-3995.00420.
   Google Scholar
• Palmgren M, Rönnqvist M, Värbrand P. 2004. A near-exact method to solve the log-truck scheduling problem. Int Tran Oper Res. 11(4):447–464. doi:10.1111/j.1475-3995.2004.00469.x.
   Google Scholar
• Parada C. 2012 June. Forestal CMPC, personal communication.
   Google Scholar
• Pillac V, Gendreau M, Guéret C, Medaglia AL. 2013. A review of dynamic vehicle routing problems. Eur J Oper Res. 225(1):1–11. doi:10.1016/j.ejor.2012.08.015.
   Web of Science ®Google Scholar
• Pulkki R. 1984. A spatial database – heuristic programming system for aiding decision-making in long-distance transport of wood. Acta Forestalia Fennica, 188.
   Google Scholar
• Rauch P. 2010. Stochastic simulation of supply chain risks in forest fuel procurement. Scand J For Res. 25(6):574–584. doi:10.1080/02827581.2010.512876.
   Google Scholar
• Rey PA, Muñoz JA, Weintraub A. 2009. A column generation model for truck routing in the Chilean forest industry. INFOR: Inf Syst Oper Res. 47(3):215–221. doi:10.3138/infor.47.3.215.
   Web of Science ®Google Scholar
• Rix G, Rousseau L-M, Pesant G. 2014. A transportation-driven approach to annual harvest planning. CIRRELT Research Document 2014-24. Canada: CIRRELT; p. 31.
   Google Scholar
• Rix G, Rousseau L-M, Pesant G. 2015. A column generation algorithm for tactical timber transportation planning. J Oper Res Soc. 66(2):278–287. doi:10.1057/jors.2013.170.
   Web of Science ®Google Scholar
• Robinson TF, 1994. Tour generation for log truck scheduling. In: 30th Annual Conference of the Operational Research Society of New Zealand; Aug-Sept 31-1; Palmerston-North, New Zealand. p. 166–171.
   Google Scholar
• Rodriguez J. 2012 June. former at Masisa, personal communication.
   Google Scholar
• Rönnqvist M, Fjeld D, Flisberg P. 2020. Developing methods for truck route selection and cost modelling in steeper topographies. For Sci. 66(4):457–468. doi:10.1093/forsci/fxz019.
   Google Scholar
• Rönnqvist M, Svenson G, Flisberg P, Jönsson L-E. 2017. Calibrated Route Finder: improving the safety, environmental consciousness, and cost effectiveness of truck routing in Sweden. Interfaces. 47(5):372–395. doi:10.1287/inte.2017.0906.
   Web of Science ®Google Scholar
• Rönnqvist M, D’Amours S, Weintraub A, Jofre A, Gunn E, Haight RG, Martell D, Murray AT, Romero C. 2015. Operational Research challenges in forestry: 33 Open Problems. Ann Oper Res. 232:11–40.
   Web of Science ®Google Scholar
• Rönnqvist M. 2012. OR challenges and experiences from solving industrial applications. Int Trans Oper Res. 19(1–2):227–251. doi:10.1111/j.1475-3995.2010.00801.x.
   Web of Science ®Google Scholar
• Rönnqvist M. 2003. Optimization in forestry. Math Program. 97(1–2):267–284. doi:10.1007/s10107-003-0444-0.
   Web of Science ®Google Scholar
• Rönnqvist M, Sahlin H, Carlsson D, 1998. Operative planning and dispatching of forestry transportation. Research paper LiTH-MAT-R-1998-18. Sweden: Linköping University.
   Google Scholar
• Rönnqvist M, Ryan D, 1995. Solving truck despatch problems in real time. In: 31th Annual Conference of the Operational Research Society of New Zealand; Aug-Sept 31-1; Wellington, New Zealand. 165–172.
   Google Scholar
• Rummukainen H, Kinnari T, Laakso M, 2009. Optimization of wood transportation. In: Madetoja E, Niskanen H, Hämäläinen J (Eds.). Papermaking Research Symposium; Jun 1-4; Kuopio, Finland: Kuopio,: University of Kuopio.
   Google Scholar
• Savola J, Rummukainen H, Jokinen O. 2004. KUORMA: a collection of APS-algorithms for forest industry wood transport. ERCIM News. 56:29–31.
   Google Scholar
• Selviaridis K, Spring M. 2007. Third party logistics: a literature review and research agenda. Int J Logist Manag. 18(1):125–150.
   Google Scholar
• Shen Z, Sessions J. 1989. Log truck scheduling by network programming. For Prod J. 39(10):47–50.
   Web of Science ®Google Scholar
• Sokolov A. 2014. Petrozavodsk State University, personal communication. Aug-Sept.
   Google Scholar
• Soriano HO. 2012 April-June. West Ingeniería Ltda, personal communication.
   Google Scholar
• Tancrez J-S, 2016. A log-truck scheduling model applied to a Belgian forest company. 6th International Conference on Information Systems, Logistics and Supply Chain (ILS); Jun 1-4, Bordeaux, France.
   Google Scholar
• Tolkki S, Koskelo I. 1993. Seeing the trees through the forest: GPS streamlines finish logging operation. USA: GPS World; Oct. p. 21–27.
   Google Scholar
• Toth P, Vigo D. Eds. 2002. The vehicle routing problem, SIAM monographs on discrete mathematics and applications. Philadelphia: Society for Industrial and Applied Mathematics.
   Google Scholar
• Visser R. 2012. University of canterbury, personal communication. Mar-Jun.
   Google Scholar
• Vitale I, Broz D, Dondo R. 2021. Optimizing log transportation in the Argentinean forest industry by column generation. For Policy Econ. 128:1–29. doi:10.1016/j.forpol.2021.102483.
   Web of Science ®Google Scholar
• Weintraub A, Epstein R, Morales R, Seron J, Traverso P. 1996. A truck scheduling system improves efficiency in the forest industries. Interfaces. 26(4):1–12. doi:10.1287/inte.26.4.1.
   Web of Science ®Google Scholar
• Weintraub A, Romero C. 2006. Operations research models and the management of agricultural and forestry resources: a review and comparison. Interfaces. 36(5):446–457. doi:10.1287/inte.1060.0222.
   Web of Science ®Google Scholar
• Weintraub A. 2012. Universidad de Chile, personal communication. Feb-Mar.
   Google Scholar
• Xu H, Chen Z-L, Rajagopal S, Arunapuram S. 2003. Solving a practical pickup and delivery problem. Transp Sci. 37(3):347–364. doi:10.1287/trsc.37.3.347.16044.
   Web of Science ®Google Scholar
• Zak J. 2010. Decision support systems in transportation. In: Jain LC, Lim CP, editors. Handbook on decision making, ISRL 4, chapter 11. Berlin, Heidelberg: Springer; p. 249–294.
   Google Scholar
• Zazgornik J, Gronalt M, Hirsch P. 2012a. A comprehensive approach to planning the deployment of transportation assets in distributing forest products. Int J Revenue Manage. 6(1/2):45–61. doi:10.1504/IJRM.2012.044515.
   Google Scholar
• Zazgornik J, Gronalt M, Hirsch P. 2012b. The combined vehicle routing and foldable container scheduling problem: a model formulation and Tabu Search based solution approaches. INFOR: Inf Syst Oper Res. 50(4):147–162. doi:10.3138/infor.50.4.147.
   Web of Science ®Google Scholar