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A Multi-objective Model for Integrated Planning of Selective Harvesting and Post-harvest Operations

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Environmental Sustainability in Asian Logistics and Supply Chains

Abstract

The paper presents an integrated planning model for selective harvesting and post-harvest processing operations with multiple objectives. A mixed integer programming model is developed to consider key operations which include harvesting, hauler assignment, processor assignment, and vehicle assignment. The first objective is to maximize profit and the second objective is to minimize the cost of lost sales. A small data set representing the operations of a company was used as the test case for model validation. The model is solved via CPLEX Optimization studio and the result of the experiment shows that the model can generate set of trade-off solutions that coordinate several related decisions in the operations, including allocation of harvesters, haulers, processors in production plant and vehicles.

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References

  1. Vorst, J. G. v. d., Silva, C. A. d., & Trienekens, J. H. (2007). Agro-industrial supply chain management: Concepts and applications. Agricultural Management, Marketing and Finance Occasional Paper.

    Google Scholar 

  2. McCreery, J., & Phillips, E. (2013). Integrated planning: The key to upstream operational excellence. Oil & Gas Financial Journal.

    Google Scholar 

  3. Grunow, M., Gunther, H.-O., & Westinner, R. (2007). Supply optimization for the production of raw sugar. International Journal of Production Economics, 110(1–2), 224–239.

    Article  Google Scholar 

  4. Ferreira, J. O., Batalha, M. O., & Domingos, J. C. (2016). Integrated planning model for citrus agribusiness system. Computers and Electronics in Agriculture, 126, 1–11.

    Article  Google Scholar 

  5. Chryssolouris, G., Chan, S., & Suh, N. (1985). An integrated approach to process planning and scheduling. CIRP Annals-Manufacturing Technology, 34(1), 413–417.

    Article  Google Scholar 

  6. Zhang, L., & Wong, T. (2016). Solving integrated process planning and scheduling problem with constructive meta-heurictics. Information Sciences, 340–341, 1–16.

    Google Scholar 

  7. Kusumastuti, R. D., van Donk, D. P., & Teunter, R. (2016). Crop-related harvesting and processing planning: A review. International Journal of Production Economics, 174, 76–92.

    Article  Google Scholar 

  8. Ahumada, O., & Villalobos, J. (2011). Operational model for planning the harvest and distribution of persihable agricultural products. International Journal of Production Economics, 133(2), 677–687.

    Article  Google Scholar 

  9. Liu, L.-L., Zhao, G.-P., Ou’yang, S.-S., & Yang, Y.-J. (2011). Integrating theory of constraints and particle swarm optimization in order planning and scheduling for machine tool production. The International Journal of Advanced Manufacturing Technology, 57(1–4), 285–295.

    Article  Google Scholar 

  10. Zhang, X.-D., & Yan, H.-S. (2005). Integrated optimization of production planning and scheduling for a kind of job-shop. The International Journal of Advanced Manufacturing Technology, 26(7–8), 876–886.

    Article  Google Scholar 

  11. Joly, M., Moro, L., & Pinto, J. (2002). Planning and scheduling for petroleum refineries using mathematical programming. Brazilian Journal of Chemical Engineering, 19(2), 207–228.

    Article  Google Scholar 

  12. Fumero, Y., Moreno, M. S., Corsano, G., & Montagna, J. M. (2016). A multi product batch design model incorporating production planning and scheduling decisions under a multiperiod scenario. Applied Mathematical Modelling, 40(5–6), 3498–3515.

    Article  Google Scholar 

  13. Bilgen, B., & Celebi, 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 

  14. Chu, Y., You, F., Wassick, J. M., & Agarwal, A. (2015). Integrated planning and scheduling under production uncertainties: Bi-level model formulation and hybrid solution method. Computers & Chemical Engineering, 72, 255–272.

    Article  Google Scholar 

  15. Sel, C., Bilgen, B., Bloemhof-Ruwaard, J., & 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 

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Correspondence to Voratas Kachitvichyanukul .

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Sornprom, T., Kachitvichyanukul, V., Luong, H.T. (2019). A Multi-objective Model for Integrated Planning of Selective Harvesting and Post-harvest Operations. In: Liu, X. (eds) Environmental Sustainability in Asian Logistics and Supply Chains. Springer, Singapore. https://doi.org/10.1007/978-981-13-0451-4_14

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