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An Approximate Dynamic Programming Approach for a Routing Problem with Simultaneous Pick-Ups and Deliveries in Urban Areas

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Food Supply Chains in Cities

Abstract

This chapter addresses vehicle routing problems with simultaneous pickups and deliveries, and time-dependent vehicle speeds, particularly confronted in the soft-drink distribution in urban areas. The conducted review provides a state-of-the-art assessment of the literature on soft-drink supply chain to reveal the recent developments. Furthermore, a real-life case is examined to address a common reverse logistics problem of collecting/reusing the reusable empty soda bottles encountered in the soft-drink industry. The problem has been formulated and solved by means of an adaptation of a recent Approximate Dynamic Programming based optimisation algorithm. The study highlights a great potential of sustainable supply chain management practices in the field. The study could be useful not only for researchers studying the topic, but also for practitioners in the soft-drink industry.

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Notes

  1. 1.

    http://www.dictionary.com/browse/sustainability, Online accessed: October 2017.

  2. 2.

    http://maps.google.com.tr, Online accessed: June 2018.

References

  • Accorsi, R., Cascini, A., Cholette, S., Manzini, R., & Mora, C. (2014). Economic and environmental assessment of reusable plastic containers: A food catering supply chain case study. International Journal of Production Economics, 152, 88–101.

    Article  Google Scholar 

  • Akkerman, R., Farahani, P., & Grunow, M. (2010). Quality, safety and sustainability in food distribution: A review of quantitative operations management approaches and challenges. OR Spectrum, 32(4), 863–904.

    Article  Google Scholar 

  • Akkerman, R., & van Donk, D. P. (2009). Product mix variability with correlated demand in two-stage food manufacturing with intermediate storage. International Journal of Production Economics, 121(2), 313–322.

    Article  Google Scholar 

  • Akkerman, R., Van Donk, D. P., & Gaalman, G. (2007). Influence of capacity-and time-constrained intermediate storage in two-stage food production systems. International Journal of Production Research, 45(13), 2955–2973.

    Article  Google Scholar 

  • Almeder, C., & Almada-Lobo, B. (2011). Synchronisation of scarce resources for a parallel machine lotsizing problem. International Journal of Production Research, 49(24), 7315–7335.

    Article  Google Scholar 

  • Almeida, C., Rodrigues, A. J. M., Agostinho, F., & Giannetti, B. F. (2017). Material selection for environmental responsibility: The case of soft-drinks packaging in Brazil. Journal of Cleaner Production, 142, 173–179.

    Article  Google Scholar 

  • Bard, J. F., & Nananukul, N. (2009). The integrated production–inventory–distribution–routing problem. Journal of Scheduling, 12(3), 257–280.

    Article  Google Scholar 

  • Bektaş, T., & Laporte, G. (2011). The pollution-routing problem. Transportation Research Part B: Methodological, 45(8), 1232–1250.

    Article  Google Scholar 

  • Bilgen, B. (2010). Application of fuzzy mathematical programming approach to the production allocation and distribution supply chain network problem. Expert Systems with Applications, 37(6), 4488–4495.

    Article  Google Scholar 

  • Bilgen, B., & Çelebi, Y. (2013). Integrated production scheduling and distribution planning in dairy supply chain by hybrid modelling. Annals of Operations Research, 211(1), 55–82.

    Article  Google Scholar 

  • Bilgen, B., & Günther, H. O. (2010). Integrated production and distribution planning in the fast moving consumer goods industry: A block planning application. OR Spectrum, 32(4), 927–955.

    Google Scholar 

  • Brandenburg, M., & Rebs, T. (2015). Sustainable supply chain management: A modeling perspective. Annals of Operations Research, 229(1), 213–252.

    Article  Google Scholar 

  • Briskorn, D., Zeise, P., & Packowski, J. (2016). Quasi-fixed cyclic production schemes for multiple products with stochastic demand. European Journal of Operational Research, 252(1), 156–169.

    Article  Google Scholar 

  • Çatay, B. (2010). A new saving-based ant algorithm for the vehicle routing problem with simultaneous pickup and delivery. Expert Systems with Applications, 37(10), 6809–6817.

    Article  Google Scholar 

  • Cha, J. H., & Roh, M. I. (2010). Combined discrete event and discrete time simulation framework and its application to the block erection process in shipbuilding. Advances in Engineering Software, 41(4), 656–665.

    Article  Google Scholar 

  • Cha, J. H., Roh, M. I., & Lee, K. Y. (2010). Integrated simulation framework for the process planning of ships and offshore structures. Robotics and Computer-Integrated Manufacturing, 26(5), 430–453.

    Article  Google Scholar 

  • Chang, P. C., & Lin, Y. K. (2010). New challenges and opportunities in flexible and robust supply chain forecasting systems. International Journal of Production Economics, 128(2), 453–456.

    Article  Google Scholar 

  • Chen, H. K., Hsueh, C. F., & Chang, M. S. (2006). The real-time time-dependent vehicle routing problem. Transportation Research Part E: Logistics and Transportation Review, 42(5), 383–408.

    Article  Google Scholar 

  • Christopher, M. (2016). Logistics & supply chain management. Pearson, UK.

    Google Scholar 

  • Çimen, M., & Kirkbride, C. (2017). Approximate Dynamic Programming algorithms for multidimensional flexible production-inventory problems. International Journal of Production Research, 55(7), 2034–2050.

    Article  Google Scholar 

  • Çimen, M., & Soysal, M. (2017). Time-dependent green vehicle routing problem with stochastic vehicle speeds: An Approximate Dynamic Programming algorithm. Transportation Research Part D: Transport and Environment, 54, 82–98.

    Article  Google Scholar 

  • Coelho, I. M., Munhoz, P. L. A., Ochi, L. S., Souza, M. J. F., Bentes, C., & Farias, R. (2016). An integrated CPU–GPU heuristic inspired on variable neighbourhood search for the single vehicle routing problem with deliveries and selective pickups. International Journal of Production Research, 54(4), 945–962.

    Article  Google Scholar 

  • Defra. (2007). Guidelines to Defra’s GHG conversion factors for company reporting—Annexes updated June 2007. Technical Report, Department for Environment, Food and Rural Affairs.

    Google Scholar 

  • Demir, E., Bektaş, T., & Laporte, G. (2011). A comparative analysis of several vehicle emission models for road freight transportation. Transportation Research Part D: Transport and Environment, 16(5), 347–357.

    Article  Google Scholar 

  • Dong, Y., Xu, K., & Evers, P. T. (2012). Transshipment incentive contracts in a multi-level supply chain. European Journal of Operational Research, 223(2), 430–440.

    Article  Google Scholar 

  • Ercin, A. E., Aldaya, M. M., & Hoekstra, A. Y. (2011). Corporate water footprint accounting and impact assessment: The case of the water footprint of a sugar-containing carbonated beverage. Water Resources Management, 25(2), 721–741.

    Article  Google Scholar 

  • Euchi, J., & Frifita, S. (2017). Hybrid metaheuristic to solve the ‘one-to-many-to-one’ problem: Case of distribution of soft-drink in Tunisia. Management Decision, 55(1), 136–155.

    Article  Google Scholar 

  • Ferreira, D., Clark, A. R., Almada-Lobo, B., & Morabito, R. (2012). Single-stage formulations for synchronised two-stage lot-sizing and scheduling in soft-drink production. International Journal of Production Economics, 136(2), 255–265.

    Article  Google Scholar 

  • Ferreira, D., Morabito, R., & Rangel, S. (2010). Relax and fix heuristics to solve one-stage one-machine lot-scheduling models for small-scale soft-drink plants. Computers & Operations Research, 37(4), 684–691.

    Article  Google Scholar 

  • Figliozzi, M. A. (2011). The impacts of congestion on time-definitive urban freight distribution networks CO2 emission levels: Results from a case study in Portland, Oregon. Transportation Research Part C: Emerging Technologies, 19(5), 766–778.

    Article  Google Scholar 

  • Figliozzi, M. A. (2012). The time dependent vehicle routing problem with time windows: Benchmark problems, an efficient solution algorithm, and solution characteristics. Transportation Research Part E: Logistics and Transportation Review, 48(3), 616–636.

    Article  Google Scholar 

  • Franceschetti, A., Honhon, D., Van Woensel, T., Bektaş, T., & Laporte, G. (2013). The time-dependent pollution-routing problem. Transportation Research Part B: Methodological, 56, 265–293.

    Article  Google Scholar 

  • Gendreau, M., Ghiani, G., & Guerriero, E. (2015). Time-dependent routing problems: A review. Computers & Operations Research, 64, 189–197.

    Article  Google Scholar 

  • Hickman, J., Hassel, D., Joumard, R., Samaras, Z., & Sorenson, S. (1999). Methodology for calculating transport emissions and energy consumption. Technical Report, Transport Research Laboratory.

    Google Scholar 

  • Iammarino, M., dell’Oro, D., Bortone, N., Mangiacotti, M., Damiano, R., & Chiaravalle, A. E. (2016). Radiostrontium levels in foodstuffs: 4-years control activity by Italian reference centre, as a contribution to risk assessment. Food Chemistry, 210, 344–354.

    Article  Google Scholar 

  • Ioannou, G. (2005). Streamlining the supply chain of the Hellenic sugar industry. Journal of Food Engineering, 70(3), 323–332.

    Article  Google Scholar 

  • Jabali, O., Van Woensel, T., & De Kok, A. G. (2012). Analysis of travel times and CO2 emissions in time-dependent vehicle routing. Production and Operations Management, 21(6), 1060–1074.

    Article  Google Scholar 

  • Jordan, W. C., & Graves, S. C. (1995). Principles on the benefits of manufacturing process flexibility. Management Science, 41(4), 577–594.

    Article  Google Scholar 

  • Kok, A. L., Hans, E. W., & Schutten, J. M. (2012). Vehicle routing under time-dependent travel times: The impact of congestion avoidance. Computers & Operations Research, 39(5), 910–918.

    Article  Google Scholar 

  • Kuo, Y. (2010). Using simulated annealing to minimize fuel consumption for the time-dependent vehicle routing problem. Computers & Industrial Engineering, 59(1), 157–165.

    Article  Google Scholar 

  • Ligterink, N. E., Tavasszy, L. A., & de Lange, R. (2012). A velocity and payload dependent emission model for heavy-duty road freight transportation. Transportation Research Part D: Transport and Environment, 17(6), 487–491.

    Article  Google Scholar 

  • Lütke Entrup, M. (2005). Advanced planning in fresh food industries: Integrating shelf life into production planning. Springer Science & Business Media.

    Google Scholar 

  • Luz, L. M., de Francisco, A. C., & Piekarski, C. M. (2015). Proposed model for assessing the contribution of the indicators obtained from the analysis of life-cycle inventory to the generation of industry innovation. Journal of Cleaner Production, 96, 339–348.

    Article  Google Scholar 

  • Malandraki, C., & Daskin, M. S. (1992). Time dependent vehicle routing problems: Formulations, properties and heuristic algorithms. Transportation Science, 26(3), 185–200.

    Article  Google Scholar 

  • Maldonado, M., Rangel, S., & Ferreira, D. (2014). A study of different subsequence elimination strategies for the soft-drink production planning. Journal of Applied Research and Technology, 12(4), 631–641.

    Article  Google Scholar 

  • Maravelias, C. T., & Sung, C. (2009). Integration of production planning and scheduling: Overview, challenges and opportunities. Computers & Chemical Engineering, 33(12), 1919–1930.

    Article  Google Scholar 

  • Meyr, H., & Mann, M. (2013). A decomposition approach for the general lotsizing and scheduling problem for parallel production lines. European Journal of Operational Research, 229(3), 718–731.

    Article  Google Scholar 

  • Modak, N. M., Panda, S., & Sana, S. S. (2016). Two-echelon supply chain coordination among manufacturer and duopolies retailers with recycling facility. International Journal of Advanced Manufacturing Technology, 87(5–8), 1531–1546.

    Article  Google Scholar 

  • Mohamadghasemi, A., & Hadi-Vencheh, A. (2011). Determining the ordering policies of inventory items in class B using if-then rules base. Expert Systems with Applications, 38(4), 3891–3901.

    Article  Google Scholar 

  • Molina-Besch, K. (2016). Prioritization guidelines for green food packaging development. British Food Journal, 118(10), 2512–2533.

    Article  Google Scholar 

  • Nardi, P. C. C., da Silva, R. L. M., Ribeiro, E. M. S., & de Oliveira, S. (2017). Proposal for a methodology to monitor sustainability in the production of soft-drinks in ref PET. Journal of Cleaner Production, 151, 218–234.

    Article  Google Scholar 

  • Parragh, S. N., Doerner, K. F., & Hartl, R. F. (2008). A survey on pickup and delivery problems. Journal für Betriebswirtschaft, 58(1), 21–51.

    Article  Google Scholar 

  • Pureza, V., Morabito, R., & Reimann, M. (2012). Vehicle routing with multiple deliverymen: Modeling and heuristic approaches for the VRPTW. European Journal of Operational Research, 218(3), 636–647.

    Article  Google Scholar 

  • Ramanathan, U. (2012). Supply chain collaboration for improved forecast accuracy of promotional sales. International Journal of Operations & Production Management, 32(5–6), 676–695.

    Article  Google Scholar 

  • Ramanathan, U., & Muyldermans, L. (2010). Identifying demand factors for promotional planning and forecasting: A case of a soft-drink company in the UK. International Journal of Production Economics, 128(2), 538–545.

    Article  Google Scholar 

  • Ramanathan, U., & Muyldermans, L. (2011). Identifying the underlying structure of demand during promotions: A structural equation modelling approach. Expert Systems with Applications, 38(5), 5544–5552.

    Article  Google Scholar 

  • Santos, M. O., Massago, S., & Almada-Lobo, B. (2010). Infeasibility handling in genetic algorithm using nested domains for production planning. Computers & Operations Research, 37(6), 1113–1122.

    Article  Google Scholar 

  • Sel, C., & Bilgen, B. (2014). Hybrid simulation and MIP based heuristic algorithm for the production and distribution planning in the soft-drink industry. Journal of Manufacturing Systems, 33(3), 385–399.

    Article  Google Scholar 

  • Sel, Ç., & Bilgen, B. (2015). Quantitative models for supply chain management within dairy industry: A review and discussion. European Journal of Industrial Engineering, 9(5), 561–594.

    Article  Google Scholar 

  • Sel, Ç., Bilgen, B., & Bloemhof-Ruwaard, J. M. (2017). Planning and scheduling of the make-and-pack dairy production under lifetime uncertainty. Applied Mathematical Modelling, 51, 129–144.

    Article  Google Scholar 

  • Sel, C., Bilgen, B., Bloemhof-Ruwaard, J. M., & van der Vorst, J. (2015). Multi-bucket optimization for integrated planning and scheduling in the perishable dairy supply chain. Computers & Chemical Engineering, 77, 59–73.

    Article  Google Scholar 

  • Shahbazkhan, M. R., Shahriari, J. E., & Najafi, M. (2012). Identifying and evaluating effective factors on lean-agile supply chain. Life Science Journal-Acta Zhengzhou University Overseas Edition, 9(3), 1951–1961.

    Google Scholar 

  • Silva, A. S., Medeiros, C. F., & Vieira, R. K. (2017). Cleaner production and PDCA cycle: Practical application for reducing the cans loss index in a beverage company. Journal of Cleaner Production, 150, 324–338.

    Article  Google Scholar 

  • Silvenius, F., Gronman, K., Katajajuuri, J. M., Soukka, R., Koivupuro, H. K., & Virtanen, Y. (2013). The role of household food waste in comparing environmental impacts of packaging alternatives. Packaging Technology and Science, 27(4), 277–292.

    Article  Google Scholar 

  • Simchi-Levi, D., & Wei, Y. (2015). Worst-case analysis of process flexibility designs. Operations Research, 63(1), 166–185.

    Article  Google Scholar 

  • Simon, B., Ben Amor, M., & Foldenyi, R. (2016). Life cycle impact assessment of beverage packaging systems: Focus on the collection of post-consumer bottles. Journal of Cleaner Production, 112, 238–248.

    Article  Google Scholar 

  • Soysal, M. (2016). Closed-loop inventory routing problem for returnable transport items. Transportation Research Part D-Transport and Environment, 48, 31–45.

    Article  Google Scholar 

  • Soysal, M., Bloemhof-Ruwaard, J. M., & Bektaş, T. (2015). The time-dependent two-echelon capacitated vehicle routing problem with environmental considerations. International Journal of Production Economics, 164, 366–378.

    Article  Google Scholar 

  • Soysal, M., Bloemhof-Ruwaard, J. M., Haijema, R., & van der Vorst, J. G. (2015). Modeling an inventory routing problem for perishable products with environmental considerations and demand uncertainty. International Journal of Production Economics, 164, 118–133.

    Article  Google Scholar 

  • Soysal, M., Bloemhof-Ruwaard, J. M., Meuwissen, M. P., & van der Vorst, J. G. (2012). A review on quantitative models for sustainable food logistics management. International Journal on Food System Dynamics, 3(2), 136–155.

    Google Scholar 

  • Soysal, M., Bloemhof-Ruwaard, J. M., & Van der Vorst, J. G. A. J. (2014). Modelling food logistics networks with emission considerations: The case of an international beef supply chain. International Journal of Production Economics, 152, 57–70.

    Article  Google Scholar 

  • Soysal, M., & Çimen, M. (2017). A simulation based restricted dynamic programming approach for the green time dependent vehicle routing problem. Computers & Operations Research, 88, 297–305.

    Article  Google Scholar 

  • Temme, E. H. M., Toxopeus, I. B., Kramer, G. F. H., Brosens, M. C. C., Drijvers, J. M. M., Tyszler, M., et al. (2014). Greenhouse gas emission of diets in the Netherlands and associations with food, energy and macronutrient intakes. Public Health Nutrition, 18(13), 2433–2445.

    Article  Google Scholar 

  • Toledo, C. F. M., de Oliveira, L., Pereira, R. D., Franca, P. M., & Morabito, R. (2014). A genetic algorithm/mathematical programming approach to solve a two-level soft-drink production problem. Computers & Operations Research, 48, 40–52.

    Article  Google Scholar 

  • Toledo, C. F. M., Kimms, A., Franca, P. M., & Morabito, R. (2015). The synchronized and integrated two-level lot-sizing and scheduling problem: Evaluating the generalized mathematical model. Mathematical Problems in Engineering, 1. Research Article. Hindawi Publishing Corporation.

    Google Scholar 

  • Villarreal, B., Sañudo, M., Duran, B., & Avila, L. (2009). A lean approach to vehicle routing. In IIE Annual Conference Proceedings, Institute of Industrial and Systems Engineers (IISE), 1096.

    Google Scholar 

  • Vlontzos, G., & Pardalos, P. M. (2017). Data mining and optimisation issues in the food industry. International Journal of Sustainable Agricultural Management and Informatics, 3(1), 44–64.

    Article  Google Scholar 

  • Wan, X., & Dresner, M. E. (2015). Closing the loop: An empirical analysis of the dynamic decisions affecting product variety. Decision Sciences, 46(6), 1141–1164.

    Article  Google Scholar 

  • Wan, X., & Sanders, N. R. (2017). The negative impact of product variety: Forecast bias, inventory levels, and the role of vertical integration. International Journal of Production Economics, 186, 123–131.

    Article  Google Scholar 

  • Zeimpekis, V., Bloemhof-Ruwaard, J. M., & Bourlakis, M. (2014). Reverse logistics in food supply chains. In Markets, business, and sustainability. Bentham Science Publishers.

    Google Scholar 

  • Zhou, Y. M., & Wan, X. (2017a). Product variety and vertical integration. Strategic Management Journal, 38(5), 1134–1150.

    Article  Google Scholar 

  • Zhou, Y. M., & Wan, X. (2017b). Product variety, sourcing complexity, and the bottleneck of coordination. Strategic Management Journal, 38(8), 1569–1587.

    Article  Google Scholar 

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Author information

Authors and Affiliations

  1. Management Science, Hacettepe University, Ankara, Turkey

    Mustafa Çimen

  2. Industrial Engineering, Karabük University, Karabuk, Turkey

    Çağrı Sel

  3. Operations Management, Hacettepe University, Ankara, Turkey

    Mehmet Soysal

Authors
  1. Mustafa Çimen
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  2. Çağrı Sel
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  3. Mehmet Soysal
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Corresponding author

Correspondence to Mustafa Çimen .

Editor information

Editors and Affiliations

  1. School of Management, Cranfield University, Cranfield, Bedfordshire, UK

    Emel Aktas

  2. School of Management, Cranfield University, Cranfield, Bedfordshire, UK

    Michael Bourlakis

Appendix A: Distances Used for the Case Study

Appendix A: Distances Used for the Case Study

Table 8 Distances in kms between the soda-filling facility (node 0) and the crossdocking points (nodes 1–10)
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Table 9 Distances between the crossdocking point in İstanbul (node 0) and the dealers in İstanbul (nodes 1–18)
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Çimen, M., Sel, Ç., Soysal, M. (2020). An Approximate Dynamic Programming Approach for a Routing Problem with Simultaneous Pick-Ups and Deliveries in Urban Areas. In: Aktas, E., Bourlakis, M. (eds) Food Supply Chains in Cities. Palgrave Macmillan, Cham. https://doi.org/10.1007/978-3-030-34065-0_4

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