Hypercube Queuing Models in Emergency Service Systems: A State-of-the-Art Review

Ghobadi, Maryam; Arkat, Jamal; Tavakkoli–Moghaddam, Reza

doi:10.24200/sci.2018.4515.0

Cited by 3 publications

(4 citation statements)

References 60 publications

(124 reference statements)

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“…Considering the overcrowding caused by differences between the processing rate of servers and arrival rate of the incoming flow in facilities, queuing approach can be a useful tool to reduce the congestion of the system as lean strategy. Ghobadi et al [30] highlighted the importance of queue system in reducing the service time and enhancing the customer satisfaction. Vahdani et al [31] applied queue system for a bi-objective SC problem including total costs and unforeseen transportation costs and used a robust optimization (RO) approach to face with uncertain parameters.…”

Section: Queue System and Uncertainty In Supply Chainmentioning

confidence: 99%

“…The following section shows the proposed multi objective mixed integer non-linear problem (MOMINLP), it should be note that equations (3), (5), (8), (16), (17), (18), (35), (36), and constraints (19), (20), (30), (33), (34) are the contributions of the model.…”

Section: Mathematical Programmingmentioning

confidence: 99%

“…The Eq. (30) indicates that the load of a vehicle varies by visiting a retailor on it's rout. The constraint (31) describes that the load of a vehicle remains constant when the vehicle does not meet the retailer u.…”

mentioning

confidence: 99%

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A hybrid metaheuristic algorithm for a data driven leagile sustainable closed-loop supply chain model under disruption risks

2020

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In the current situation, taking into consideration the environmental and social issues are related with the production and distribution of products in supply chain systems, due to the global concerns related with emitting lots of greenhouse gases within the manufacturing process and overlooking the major needs of public. This paper proposes a new multi objective model in the area of closed loop supply chain problem integrated with lot sizing by considering lean, agility and sustainability factors simultaneously. Next, a robust possibilistic programming approach is applied to handle the uncertainty of the model. To increase the responsiveness of the system, a fuzzy c-means clustering method is applied to select the potential locations based on the proximity to local customers. In the following, a new hybrid metaheuristic algorithm is developed to deal with large size problems efficiency and to assess the impact of using a single-based initial solution as the income for the second phase of the proposed hybrid algorithm. To ensure about the effectiveness of the proposed algorithm, another well-known metaheuristic algorithm is developed too. The results reached from experiments on different test problems approve the superiority of the hybrid metaheuristic algorithm to find better solutions.

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Section: Queue System and Uncertainty In Supply Chainmentioning

confidence: 99%

Section: Mathematical Programmingmentioning

confidence: 99%

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A hybrid metaheuristic algorithm for a data driven leagile sustainable closed-loop supply chain model under disruption risks

2020

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“…When the status of an ambulance changes from idle to busy or vice versa, it enters or exits a state. For a better understanding of hypercube models, see Ghobadi et al, 2 who presented a comprehensive review of hypercube models and their applications in location problems.…”

Section: Introductionmentioning

confidence: 99%

A simulation-optimization algorithm for return strategies in emergency medical systems

et al. 2021

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In an emergency medical system, the locations of ambulance stations has a direct impact on response time. In this paper, two location models are presented in combination with the hypercube queuing model to maximize coverage probability. In the first model, the locations of free and busy ambulances are considered in the system states, and the hypercube model can be analyzed accurately. The model contains a large number of states, and cannot be used for large-sized problems. For this reason, the second model is presented with the same assumptions as in the first model, except that the locations of busy ambulances are not included in the system state, but approximated based on the arrival rates. Both models are offline and dynamic, in which an ambulance does not necessarily return to the station from which it has been dispatched. Two strategies are defined for returning ambulances to the stations from the customer’s location. In the first strategy, the ambulance is returned to the nearest station after completion of its mission, and in the second strategy, it returns to the empty station that covers the highest demand rate. For evaluation of the performance of the proposed models, small-sized examples are solved for both return strategies using the GAMS software. A simulation-optimization approach combined with a simulated annealing algorithm and a discrete-event simulation are used for solving large-sized problems. Moreover, real data from a case study are used to demonstrate the performance of the models in the real world.

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A Novel Birth and Death Chain Formulation and Solution to a Spatial Queuing Problem

2019

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Hypercube Queuing Models in Emergency Service Systems: A State-of-the-Art Review

Cited by 3 publications

References 60 publications

A hybrid metaheuristic algorithm for a data driven leagile sustainable closed-loop supply chain model under disruption risks

A hybrid metaheuristic algorithm for a data driven leagile sustainable closed-loop supply chain model under disruption risks

A simulation-optimization algorithm for return strategies in emergency medical systems

A Novel Birth and Death Chain Formulation and Solution to a Spatial Queuing Problem

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