An M/M/C/K queueing system in an inventory routing problem considering congestion and response time for post-disaster humanitarian relief: a case study

Abstract

PurposeDue to the randomness and unpredictability of many disasters, it is essential to be prepared to face difficult conditions after a disaster to reduce human casualties and meet the needs of the people. After the disaster, one of the most essential measures is to deliver relief supplies to those affected by the disaster. Therefore, this paper aims to assign demand points to the warehouses as well as routing their related relief vehicles after a disaster considering convergence in the border warehouses.Design/methodology/approachThis research proposes a multi-objective, multi-commodity and multi-period queueing-inventory-routing problem in which a queuing system has been applied to reduce the congestion in the borders of the affected zones. To show the validity of the proposed model, a small-size problem has been solved using exact methods. Moreover, to deal with the complexity of the problem, a metaheuristic algorithm has been utilized to solve the large dimensions of the problem. Finally, various sensitivity analyses have been performed to determine the effects of different parameters on the optimal response.FindingsAccording to the results, the proposed model can optimize the objective functions simultaneously, in which decision-makers can determine their priority according to the condition by using the sensitivity analysis results.Originality/valueThe focus of the research is on delivering relief items to the affected people on time and at the lowest cost, in addition to preventing long queues at the entrances to the affected areas.

A scenario-based collaborative problem for a relief supply chain during post-disaster under uncertain parameters: a real case study in Dorud

“…Besides, information based on the search region can be replaced among multiple solutions, bringing about a rapid motion to optimum goals. Therefore, given its benefits and its favorable performance, verified in some studies (Abazari et al , 2021; Masoumi et al , 2021), it can be stated that GOA can be efficient in solving real-world cases with unknown search spaces (Malekkhouyan et al , 2021).…”

Designing a post-disaster humanitarian supply chain using machine learning and multi-criteria decision-making techniques

“…Relief activities in the humanitarian supply chain are managed by several actors (Van Wassenhove, 2006). To the best of our knowledge, humanitarian operations require a comprehensive crisis management plan, but many countries cannot afford a proper plan due to economic limits (Maghsoudi et al, 2018;Masoumi et al, 2022). Oloruntoba and Gray (2006) combined the concepts of the academic supply chain literature with humanitarian aids to optimize the humanitarian operations.…”

“…Relief activities in the humanitarian supply chain are managed by several actors (Van Wassenhove, 2006). To the best of our knowledge, humanitarian operations require a comprehensive crisis management plan, but many countries cannot afford a proper plan due to economic limits (Maghsoudi et al ., 2018; Masoumi et al. , 2022).…”

A novel mathematical model to minimize the total cost of the hospital and COVID-19 outbreak concerning waiting time of patients using Jackson queueing networks, a case study

“…GOA is a kind of constructive algorithm capable of large-scale and real-world problems on any scale. GOA has prepared for continuous spaces, so it is essential to continuously create initial solutions in discrete spaces so that exploration and exploitation operators work better [42,43].…”