PL EN


Preferencje help
Widoczny [Schowaj] Abstrakt
Liczba wyników
Tytuł artykułu

Decision support for allocating farmed fish to customer orders using a bi-objective optimization model

Treść / Zawartość
Identyfikatory
Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
Aquaculture is an important industry in certain coastal areas. Focusing on farming of salmon and trout, an operational planning problem arises with the goal of allocating supply of fish to demand expressed through customer orders. This paper provides a conceptual model of such a planning problem, defines a corresponding bi-objective mathematical programming model. The problem is novel with respect to the structure of the transportation of fish, and the rules for satisfying customer orders with respect to fish size, quality, certification, and health status. Computational experiments are conducted to gain further insights into the use of the provided model to provide support for planners involved in the operational decision making. Results indicate that the bi-objective optimization model can be useful in situations where supply is insufficient to cover all the demand within a given planning horizon.
Rocznik
Tom
Strony
67--90
Opis fizyczny
Bibliogr. 28 poz., rys., tab., wykr.
Twórcy
  • Molde University College, Faculty of Logistics, Norway
autor
  • Molde University College, Faculty of Logistics, Norway
autor
  • Molde University College, Faculty of Logistics, Norway
  • Molde University College, Faculty of Logistics, Norway
autor
  • Molde University College, Faculty of Logistics, Norway
Bibliografia
  • Abdollahi Saadatlu E., Barzinpour F. & Yaghoubi S. (2022). A sustainable model for municipal solid waste system considering global warming potential impact: A case study. Computers & Industrial Engineering,169, art. no. 108127. doi: 10.1016/j.cie.2022.108127.
  • Abedi A. & Zhu W. (2017). An optimisation model for purchase, production anddistribution in fish supply chain – A case study. International Journal of Production Research,55(12), pp. 3451–3464. doi: 10.1080/00207543.2016.1242800.
  • Ahumada O. & Villalobos J.R. (2009). Application of planning models in the agrifood supply chain: A review. European Journal of Operational Research,196(1), pp. 1–20. doi: 10.1016/j.ejor.2008.02.014.
  • Ahumada O. & Villalobos J.R. (2011). Operational model for planning the harvest and distribution of perishable agricultural products. International Journal of Production Economics,133(2), pp. 677–687. doi: 10.1016/j.ijpe.2011.05.015.
  • Amorim P., Günther H.-O. & Almada-Lobo B. (2012). Multi-objective integrated production and distribution planning of perishable products. International Journalof Production Economics,138(1), pp. 89–101. doi: 10.1016/j.ijpe.2012.03.005.
  • Chowdhury M. & Tan P. (2004). A multi-objective decision-making framework fortransportation investments. Journal of the Transportation Research Forum, 43(1), pp. 91–104. doi: 10.22004/ag.econ.206723.
  • Ebrahimi S. & Bagheri E. (2022). Optimizing profit and reliability using a biobjective mathematical model for oil and gas supply chain under disruption risks. Computers & Industrial Engineering,163(100), art. no. 107849. doi: 10.1016/j.cie.2021.107849.
  • Fan Z., Li S. & Gao Z. (2019). Multiobjective sustainable order allocation problem optimization with improved genetic algorithm using priority encoding. Mathematical Problems in Engineering, 2019, art. no. 8218709. doi: 10.1155/2019/8218709.
  • Fasihi M., Tavakkoli-Moghaddam R., Najafi S. & Hajiaghaei M. (2021a). Optimizinga biobjective multi-period fish closed-loop supply chain network design by threemulti-objective meta-heuristic algorithms. Scientia Iranica.doi: 10.24200/sci.2021.57930.5477.
  • Fasihi M., Tavakkoli-Moghaddam R., Najafi S. & Hajiaghaei-Keshteli M. (2021b). Developing a biobjective mathematical model to design the fish closed-loop supplychain. International Journal of Engineering,34(5), pp. 1257–1268. doi: 10.5829/ije.2021.34.05b.19.
  • Ghasemi P., Khalili-Damghani K., Hafezalkotob A. & Raissi S. (2019). Uncertainmulti-objective multi-commodity multi-period multi-vehicle location-allocation model for earthquake evacuation planning. Applied Mathematics and Computation,350(100), pp. 105–132.doi: 10.1016/j.amc.2018.12.061.
  • Gholizadeh H., Jahani H., Abareshi A. & Goh M. (2021). Sustainable closed-loop supply chain for dairy industry with robust and heuristic optimization. Computers & Industrial Engineering,157, art. no. 107324. doi: 10.1016/j.cie.2021.107324.
  • Hwang C.-L. & Masud A.S.M. (1979). Multiple Objective Decision Making. A State-of-the-Art Survey. Springer Verlag. doi: 10.1007/978-3-642-45511-7.
  • Jia R., Liu Y. & Bai X. (2020). Sustainable supplier selection and order allocation: Distributionally robust goal programming model and tractable approximation. Computers & Industrial Engineering,140, art. no. 106267. doi: 10.1016/j.cie.2020.106267.
  • Kaviani M.A., Peykam A., Khan S.A., Brahimi N. & Niknam R. (2020). A new weighted fuzzy programming model for supplier selection and order allocation in the food industry. Journal of Modelling in Management, 15(2), pp. 381-406. doi: 10.1108/JM2-11-2018-0191.
  • Kiwa Norway (2021). Mattrygghet og akvakultur [in Norwegian]. https://www.kiwa.com/no/no/vaare-tjenester/sertifisering/mattrygghet-og-akvakultur/ [10.05.2021].
  • Koldborg Jensen T., Nielsen J., Larsen E.P. & Clausen J. (2010). The fish industry - toward supply chain modeling. Journal of Aquatic Food Product Technology, 19(3–4), pp. 214–226. doi: 10.1080/10498850.2010.508964.
  • Mavrotas G. (2009). Effective implementation of theε-constraint method in Multi-Objective Mathematical Programming problems. Applied Mathematics and Computation,213(2), pp. 455–465. doi: 10.1016/j.amc.2009.03.037.
  • Moheb-Alizadeh H. & Handfield R. (2019). Sustainable supplier selection and order allocation: A novel multi-objective programming model with a hybrid solution approach. Computers & Industrial Engineering, 129, pp. 192–209. doi: 10.1016/j.cie.2019.01.011.
  • Mosallanezhad B., Hajiaghaei-Keshteli M. & Triki C. (2021). Shrimp closed-loop supply chain network design. Soft Computing, 25(11), pp. 7399–7422. doi: 10.1007/s00500-021-05698-1.
  • Musavi M. & Bozorgi-Amiri A. (2017). A Multi-objective sustainable hub location-scheduling problem for perishable food supply chain.Computers & Industrial Engineering, 113(100), pp. 766–778. doi: 10.1016/j.cie.2017.07.039.
  • Norwegian Food Safety Authority (2020).Fish health. https://www.mattilsynet.no/fisk_og_akvakultur/fiskehelse/[10.05.2021].
  • NOU (2019). Skattlegging av havbruksvirksomhet. Taxation of aquaculture activities, Finans departement.
  • Rabbani M., Amirhossein Sadati S. & Farrokhi-Asl H. (2020). Incorporating locationrouting model and decision making techniques in industrial waste management: Application in the automotive industry. Computers & Industrial Engineering,148, art. no. 106692. doi: 10.1016/j.cie.2020.106692.
  • Seitz A., Grunow M. & Akkerman R. (2020). Data driven supply allocation to individual customers considering forecast bias. International Journal of Production Economics, 227, art. no. 107683. doi: 10.1016/j.ijpe.2020.107683.
  • Sharma R. & Darbari J.D. (2021). Integrated optimization model for sustainable supplier selection and order allocation in food supply chain. In: A. Tiwari, K. Ahuja,A. Yadav, J.C. Bansal, K. Deep & A.K. Nagar (Eds.). Soft Computing for Problem Solving, Springer, pp. 557–572.
  • Wang S. & Ma S. (2018). Efficient methods for a biobjective nursing home locationand allocation problem: A case study. Applied Soft Computing, 65, pp. 280–291. doi: 10.1016/j.asoc.2018.01.014.
  • Zhang Z., Guo C., Ruan W., Wang W. & Zhou P. (2022). An intelligent stochastic optimization approach for stochastic order allocation problems with high-dimensional order uncertainties. Computers & Industrial Engineering,167, art. no. 108008. doi: 10.1016/j.cie.2022.108008.
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-399fddd5-00ca-48ff-8f57-86d7fef20e5e
JavaScript jest wyłączony w Twojej przeglądarce internetowej. Włącz go, a następnie odśwież stronę, aby móc w pełni z niej korzystać.