Optimisation model for a chain logistics problem involving chilled food under conditions of uncertainty

• Autorzy: Taghinezhad Yaser

Identyfikatory

DOI

10.5277/ord190207

• Języki publikacji: EN

Abstrakty

EN

In the last two decades, food safety has become one of the main concerns in the area of logistics and supply chain management and also in the refrigeration or freezing of goods. Safety is a critically sensitive area in this field, as if the required safety conditions are not satisfied during the logistics process, foods will soon deteriorate and probably become unsafe for consumption by customers. Thus, the problem of ensuring the safety of chilled food has received serious attention among logistics practitioners. However, because of the complex nature of such problems, research so far has been limited to quantitative models with deterministic parameters and the robustness of the results from such models should be examined. In this paper, a robust optimisation model has been developed with the aim of optimising food safety aspects and thus minimising the logistics cost of a chilled chain system under various types of uncertainty and constraints on customers’ time windows. Realizations of the model are solved by an algorithm based on artificial bee colony intelligence using MATLAB R2016a software. Finally, the results are analysed for possible real world considerations in order to propose some key practical highlights.

Słowa kluczowe

EN

artificial intelligence; supply; chilled foods; logistics; uncertainty

PL

sztuczna inteligencja; dostawa; żywność schłodzona; logistyka; niepewność

• Wydawca: Oficyna Wydawnicza Politechniki Wrocławskiej
• Czasopismo: Operations Research and Decisions
• Rocznik: 2019
• Tom: Vol. 29, No. 2
• Strony: 103--116
• Opis fizyczny: Bibliogr. 21 poz., rys.

Twórcy

autor

Taghinezhad Yaser

• Graduated from Industrial Management, Faculty of Management and Accounting of Farabi, University of Tehran, Iran

Bibliografia

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Uwagi

Opracowanie rekordu w ramach umowy 509/P-DUN/2018 ze środków MNiSW przeznaczonych na działalność upowszechniającą naukę (2019).