In this paper, a multi-objective multi-period sustainable location-allocation supply chain network model will be presented. Different levels of technology for vehicle fleet, which leads to differen...

A hybrid robust possibilistic approach for a sustainable supply chain location-allocation network design

As a service-oriented supply chain, blood supply chain management deals with a human-to-human network involved with a number of direct challenges such as irregularity in both blood supply and demand as well as multiplicity of blood products, their respective lifetimes and perishability. Besides, facing risks originating from natural disasters or man-made incidents such as labor strikes, economic problems, and so on, and from uncertainty embedded in the input data is also a real highlight in designing and managing a blood supply chain network. This paper addresses an enhanced perspective incorporating a two-phase preemptive policy by which the disruption risk is diminished through a hybrid technique using the fuzzy analytic hierarchy process and grey rational analysis for determining supplementary blood facilities, to cooperate in production process and decrease interruptions. Furthermore, a p-robust formulation is presented to control the network reliability under disruption scenarios at minimum cost. To protect the network against the uncertainty, a consolidated approach based on a recently developed fuzzy measure is extended. We also examine the validity and practicality of the proposed model and its solution perspective along with the reliability of the network by a real case of Iran. It is worth nothing that the problems in the case of disasters in which the impact of the two risk streams will be felt most keenly, could benefit from the proposed procedure advantages since it develops a proactive and controlling approach which can be extensively applicable in disastrous situation.

An enhanced procedure for managing blood supply chain under disruptions and uncertainties

Green-blood supply chain network design: Robust optimization, bounded objective function & Lagrangian relaxation

This paper addresses an integrated relief network design problem for pharmaceutical items. The proposed bi-objective model accounts for perishability of pharmaceutical items, mobility of relief facilities, and benefits from a cooperative coverage mechanism in designing the network. A min–max robust model is developed to tackle the demand uncertainty. Several numerical experiments are conducted to explore the performance of the robust model. Also, by conducting a real case study, useful managerial insights are derived through performing several sensitivity analyses. The numerical results reveal that using the min–max robust model enhances the pharmaceutical relief network’s effectiveness and efficiency considerably.

Designing an integrated pharmaceutical relief chain network under demand uncertainty

https://onlinelibrary.wiley.com/doi/epdf/10.1111/itor.12714

A mixed resilient‐efficient approach toward blood supply chain network design

Health service network design: a robust possibilistic approach

This paper addresses a multi-period three-level health service network redesign problem. The problem involves strategic decisions on locating, closing or expanding the capacity of network’s facilities over the planning horizon, (re)designing an efficient referral system and (re)allocating patient zones to facilities while aiming at achieving an accessible, stable, and equitable network. A robust mixed possibilistic-flexible programming approach is devised to cope with imprecise parameters and soft constraints. Afterwards an improved augmented e-constraint method is proposed to find the Pareto front. Finally, a real case study is provided to illustrate the performance of the proposed model and its solution procedure.

F. Abolhassani

Papers

Health service network design: a robust possibilistic approach

Accessible, stable, and equitable health service network redesign: A robust mixed possibilistic-flexible approach