The design and planning of an integrated supply chain for perishable products under uncertainties

Abstract

Purpose This paper aims to design an optimal supply chain network and to develop a suitable distribution planning under uncertainty for perishable product's supply chain. The ultimate goal is to help in making decisions under uncertain environments. Design/methodology/approach In this paper, stochastic programming is used under conditions of demand, supply and process uncertainties, and a non-linear mathematical model is developed for perishable product’s supply chain. Authors’ study considers disruptions in transportation routes and also within the facilities and investigates optimal facility location and shipment decisions while minimising the total supply chain cost. A scenario-based approach is used to model these disruptions. The retailer level uncertainty due to demand-supply mismatch is handled by incorporating the newsvendor model into the last echelon of supply chain network. In this paper, two policies are proposed for making decisions under uncertain environments. In the first one, the expected cost of the supply chain is minimised. To also consider the risk behaviour of the decision maker, authors propose the second policy through a conditional value-at-risk approach. Findings Authors discuss the model output through various examples that are provided via a case study from the milk industry. The supply chain design and planning of the disruption-free model are different from those of the resilient model. Practical implications Authors’ research benefits the perishable products industries which encounter the disruption problems in their transportation routes as well as in the facilities. Authors have demonstrated the research through a real-life case in a milk industry. Originality/value The major contribution of authors’ work is the design of the supply chain network under disruption risks by incorporating aspects of product perishability. This work provides insight into areas such as the simultaneous consideration of demand, supply and process uncertainties. The amalgamation of newsvendor model and the approximation of the non-linearity of retailer level cost function especially in the context of supply chain under uncertainty is the first of its kind. We provide a comprehensive statistical study of uncertainties that are present in the supply chain in a unique manner.

Sustainable supply chain management towards disruption and organizational ambidexterity: A data driven analysis

“… I22 Uncertainty “Uncertainty” refers to a state that cannot be directly expressed by a certain amount of information, which describes a situation that cannot be ascertained, or where there are different possibilities. Liao et al (2019); Sato et al (2020) ; Samani et al (2020) ; Goodarzian et al (2020) ; Sureeyatanapas et al (2020) ; Dutta & Shrivastava (2020) ; Paul et al (2020) ; Fattahi & Govindan (2020) ; Darby et al (2020) ; Soren & Shastri (2019) ; Salehi et al (2019) ; Xiao et al (2019) ; Uddin & Huynh (2019) ; Pashapour et al (2019) ; Diabat et al (2019) ; Alvarado-Vargas & Kelley (2019) ; Sreedevi & Saranga (2017) . …”

Multi-Objective Optimization Models for Sustainable Perishable Intermodal Multi-Product Networks with Delivery Time Window

“…In the article by de Kaize et al [26]., the heterogeneity in quality deterioration of different products under different temperature conditions is controlled through a MIP model which includes decisions about hubs location, process, and inventory. Dutta and Shrivastava's work presents a non-linear model for a threeechelon supply chain with suppliers, processors, and consumers [27]. Under uncertain conditions, the study proposes a supply chain policy to optimize costs when the risk parameters are both low and high.…”

“…Constraints (27) ensures that the number of employee and the shipped quantity are integer variables. Meanwhile, all of the decision variables in this MIP model are nonnegative.…”

Resilient Strategies and Sustainability in Agri-Food Supply Chains in the Face of High-Risk Events

“…Redesigning the supply chain towards market adaptation [36], [37], [39], [41], [43], [45] ✓ ✓ ✓ P: proactive; C: concurrent; R: reactive; S: supply; D: demand Considering the supplier-manufacturer relationship to be paramount, strategies of stock security, redundancy, and diversification in the stocking of raw materials [33]- [36], select flexible and agile suppliers with product support capabilities and geographic dispersion [27], [33]- [39] and implementation of special supplier contracting methodology for critical suppliers, multiple suppliers and substitute suppliers [27], [33]- [35], [37]. These strategies should be implemented at the prevention stage considering the vulnerability of the focal company and its suppliers [21].…”

“…Considering the focal company, fortification strategies in supply chain design that allow for production flexibility and production rescheduling [37], [38], [40], [41] and that increase robustness by introducing production redundancy, excessive inventories and security stocks [42] are proposed. These strategies allow supporting the disruptive event and keeping the productive process adapted to the new reality.…”