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Multi-Period Mixed Integer Programming Model for Supply Chain Planning Under Safety Stock

Yıl 2020, Cilt: 2 Sayı: 2, 44 - 49, 31.12.2020

Ahmet Aktas İzzettin Temiz

https://doi.org/10.47512/meujmaf.816402

Öz

Supply chain management philosophy has been adopted by enterprises due to the requirement of customer demand satisfaction in reasonable times under market competition. In case of rapid increase in product demands and/or occurrence of supply problems in materials, enterprises choose holding some amount of safety stock of several materials and products. In this study, a multi-period, multi-product supply chain with different suppliers, material storages, production plants, distribution centers and customers is modeled. To determine the optimal production, supply and storage plans at minimum cost, a mixed-integer programming model is proposed. Capacity, bill-of-materials structure of products and placement of safety stocks are taken into account within the proposed model. Solutions of a set of examples are also presented in order to test the model.

Anahtar Kelimeler

Supply chain Safety stock Integer programming Bill-of-materials

Kaynakça

  • Aktas, A., Temi̇z, İ. (2020). “Goal Programming Model for Production-Distribution Planning by Considering Carbon Emission”. Gazi University Journal of Science, Vol. 33, No. 1, pp. 135-150 .
  • Aliev, R. A., Fazlollahi, B., Guirimov, B. G., Aliev, R. R., (2007), “Fuzzy-genetic approach to aggregate production–distribution planning in supply chain management”, Information Sciences, Vol. 177, pp. 4241-4255.
  • Cóccola M. O., Méndez, C. A., Dondo, R. G., (2020), “A two-stage procedure for efficiently solving the integrated problem of production, inventory, and distribution of industrial products”, Computers and Chemical Engineering, 134, 106690
  • Costantino, N., Dotoli, M., Falagario, M., Fanti, M. P., Mangini, A. M., (2012), “A model for supply management of agile manufacturing supply chains”. International Journal of Production Economics, Vol. 135, pp. 451-457.
  • Ghadimi F., Aouam, T., (2021), “Planning capacity and safety stocks in a serial production–distribution system with multiple products, European Journal of Operational Research, 289, pp. 533–552.
  • Graves, S. C., Willems, S. P., (2005), “Optimizing the Supply Chain Configuration for New Products”, Management Science, Vol. 51, pp. 1165-1180.
  • Guarnaschelli, A., Salomone H. E., Méndez, C. A., (2020). “A stochastic approach for integrated production and distribution planning in dairy supply chains”, Computers & Chemical Engineering, 140, 106966.
  • Khalifehzadeh, S., Seifbarghy, M., Naderi, B., (2017), “Solving a fuzzy multi objective model of a production–distribution system using meta-heuristic based approaches”. Journal of Intelligent Manufacturing, Vol. 28, pp. 95-109.
  • Lakhal, S., Martel, A., Kettani, O., Oral, M., (2001), “On the optimization of supply chain networking decisions”, European Journal of Operational Research, Vol. 129, pp. 259-270.
  • Liang, T.-F., (2008), “Fuzzy multi-objective production/distribution planning decisions with multi-product and multi-time period in a supply chain”, Computers & Industrial Engineering, Vol. 55, pp. 676-694.
  • Miranda, P. L., Morabito, R., Ferreira, D., (2018). “Optimization model for a production, inventory, distribution and routing problem in small furniture companies”. TOP, Vol. 26, pp. 30-67.
  • Paksoy, T., Özceylan, E., Weber, G.-W., (2012), “Profit oriented supply chain network optimization”, Central European Journal of Operations Research, Vol. 21, pp. 455-478.
  • Rafiei, H., Safaei, F., Rabbani M., (2018)., “Integrated production-distribution planning problem in a competition-based four-echelon supply chain”. Computers & Industrial Engineering, Vol. 119, pp. 85–99.
  • Romeijn, H. E., Shu, J., Teo, C.-P., (2007), “Designing two-echelon supply networks”, European Journal of Operational Research, Vol. 178, pp. 449-462.
  • Santoso, T., Ahmed, S., Goetschalckx, M., Shapiro, A., (2005), “A stochastic programming approach for supply chain network design under uncertainty”, European Journal of Operational Research, Vol. 167, pp. 96-115.
  • Sha, D. Y., Che, Z. H., (2004), “Virtual integration with a multi-criteria partner selection model for the multi-echelon manufacturing system”, The International Journal of Advanced Manufacturing Technology, Vol. 25, pp. 793-802.
  • Torabi, S. A., Hassini, E., (2009), “Multi-site production planning integrating procurement and distribution plans in multi-echelon supply chains: an interactive fuzzy goal programming approach”, International Journal of Production Research, Vol. 47, pp. 5475-5499.
  • Tsiakis, P., Papageorgiou, L. G., (2008), “Optimal production allocation and distribution supply chain networks”, International Journal of Production Economics, Vol. 111, pp. 468-483.

Yıl 2020, Cilt: 2 Sayı: 2, 44 - 49, 31.12.2020

Ahmet Aktas İzzettin Temiz

https://doi.org/10.47512/meujmaf.816402

Öz

Kaynakça

  • Aktas, A., Temi̇z, İ. (2020). “Goal Programming Model for Production-Distribution Planning by Considering Carbon Emission”. Gazi University Journal of Science, Vol. 33, No. 1, pp. 135-150 .
  • Aliev, R. A., Fazlollahi, B., Guirimov, B. G., Aliev, R. R., (2007), “Fuzzy-genetic approach to aggregate production–distribution planning in supply chain management”, Information Sciences, Vol. 177, pp. 4241-4255.
  • Cóccola M. O., Méndez, C. A., Dondo, R. G., (2020), “A two-stage procedure for efficiently solving the integrated problem of production, inventory, and distribution of industrial products”, Computers and Chemical Engineering, 134, 106690
  • Costantino, N., Dotoli, M., Falagario, M., Fanti, M. P., Mangini, A. M., (2012), “A model for supply management of agile manufacturing supply chains”. International Journal of Production Economics, Vol. 135, pp. 451-457.
  • Ghadimi F., Aouam, T., (2021), “Planning capacity and safety stocks in a serial production–distribution system with multiple products, European Journal of Operational Research, 289, pp. 533–552.
  • Graves, S. C., Willems, S. P., (2005), “Optimizing the Supply Chain Configuration for New Products”, Management Science, Vol. 51, pp. 1165-1180.
  • Guarnaschelli, A., Salomone H. E., Méndez, C. A., (2020). “A stochastic approach for integrated production and distribution planning in dairy supply chains”, Computers & Chemical Engineering, 140, 106966.
  • Khalifehzadeh, S., Seifbarghy, M., Naderi, B., (2017), “Solving a fuzzy multi objective model of a production–distribution system using meta-heuristic based approaches”. Journal of Intelligent Manufacturing, Vol. 28, pp. 95-109.
  • Lakhal, S., Martel, A., Kettani, O., Oral, M., (2001), “On the optimization of supply chain networking decisions”, European Journal of Operational Research, Vol. 129, pp. 259-270.
  • Liang, T.-F., (2008), “Fuzzy multi-objective production/distribution planning decisions with multi-product and multi-time period in a supply chain”, Computers & Industrial Engineering, Vol. 55, pp. 676-694.
  • Miranda, P. L., Morabito, R., Ferreira, D., (2018). “Optimization model for a production, inventory, distribution and routing problem in small furniture companies”. TOP, Vol. 26, pp. 30-67.
  • Paksoy, T., Özceylan, E., Weber, G.-W., (2012), “Profit oriented supply chain network optimization”, Central European Journal of Operations Research, Vol. 21, pp. 455-478.
  • Rafiei, H., Safaei, F., Rabbani M., (2018)., “Integrated production-distribution planning problem in a competition-based four-echelon supply chain”. Computers & Industrial Engineering, Vol. 119, pp. 85–99.
  • Romeijn, H. E., Shu, J., Teo, C.-P., (2007), “Designing two-echelon supply networks”, European Journal of Operational Research, Vol. 178, pp. 449-462.
  • Santoso, T., Ahmed, S., Goetschalckx, M., Shapiro, A., (2005), “A stochastic programming approach for supply chain network design under uncertainty”, European Journal of Operational Research, Vol. 167, pp. 96-115.
  • Sha, D. Y., Che, Z. H., (2004), “Virtual integration with a multi-criteria partner selection model for the multi-echelon manufacturing system”, The International Journal of Advanced Manufacturing Technology, Vol. 25, pp. 793-802.
  • Torabi, S. A., Hassini, E., (2009), “Multi-site production planning integrating procurement and distribution plans in multi-echelon supply chains: an interactive fuzzy goal programming approach”, International Journal of Production Research, Vol. 47, pp. 5475-5499.
  • Tsiakis, P., Papageorgiou, L. G., (2008), “Optimal production allocation and distribution supply chain networks”, International Journal of Production Economics, Vol. 111, pp. 468-483.
Toplam 18 adet kaynakça vardır.

Ayrıntılar

Birincil Dil İngilizce
Konular Yöneylem
Bölüm Research Articles
Yazarlar

Ahmet Aktas 0000-0002-4394-121X

İzzettin Temiz 0000-0001-8672-1340

Yayımlanma Tarihi 31 Aralık 2020
Gönderilme Tarihi 26 Ekim 2020
Yayımlandığı Sayı Yıl 2020 Cilt: 2 Sayı: 2

Kaynak Göster

APA Aktas, A., & Temiz, İ. (2020). Multi-Period Mixed Integer Programming Model for Supply Chain Planning Under Safety Stock. Mersin University Journal of Maritime Faculty, 2(2), 44-49. https://doi.org/10.47512/meujmaf.816402
AMA Aktas A, Temiz İ. Multi-Period Mixed Integer Programming Model for Supply Chain Planning Under Safety Stock. MEUJMAF. Aralık 2020;2(2):44-49. doi:10.47512/meujmaf.816402
Chicago Aktas, Ahmet, ve İzzettin Temiz. “Multi-Period Mixed Integer Programming Model for Supply Chain Planning Under Safety Stock”. Mersin University Journal of Maritime Faculty 2, sy. 2 (Aralık 2020): 44-49. https://doi.org/10.47512/meujmaf.816402.
EndNote Aktas A, Temiz İ (01 Aralık 2020) Multi-Period Mixed Integer Programming Model for Supply Chain Planning Under Safety Stock. Mersin University Journal of Maritime Faculty 2 2 44–49.
IEEE A. Aktas ve İ. Temiz, “Multi-Period Mixed Integer Programming Model for Supply Chain Planning Under Safety Stock”, MEUJMAF, c. 2, sy. 2, ss. 44–49, 2020, doi: 10.47512/meujmaf.816402.
ISNAD Aktas, Ahmet - Temiz, İzzettin. “Multi-Period Mixed Integer Programming Model for Supply Chain Planning Under Safety Stock”. Mersin University Journal of Maritime Faculty 2/2 (Aralık 2020), 44-49. https://doi.org/10.47512/meujmaf.816402.
JAMA Aktas A, Temiz İ. Multi-Period Mixed Integer Programming Model for Supply Chain Planning Under Safety Stock. MEUJMAF. 2020;2:44–49.
MLA Aktas, Ahmet ve İzzettin Temiz. “Multi-Period Mixed Integer Programming Model for Supply Chain Planning Under Safety Stock”. Mersin University Journal of Maritime Faculty, c. 2, sy. 2, 2020, ss. 44-49, doi:10.47512/meujmaf.816402.
Vancouver Aktas A, Temiz İ. Multi-Period Mixed Integer Programming Model for Supply Chain Planning Under Safety Stock. MEUJMAF. 2020;2(2):44-9.
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