A robust fuzzy stochastic model for the responsive-resilient inventory-location problem: comparison of metaheuristic algorithms

Nayeri, Sina; Tavakoli, Mahdieh; Tanhaeean, Mehrab; Jolai, Fariborz

doi:10.1007/s10479-021-03977-6

Cited by 24 publications

(16 citation statements)

References 55 publications

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“…In this research, to consider the high level of uncertainty and improve the system performance for tackling the uncertainty, we investigate the research problem under the mixed uncertainty (based on randomness and epistemic uncertainties). Considering this point not only brings the studied problem closer to real-world conditions but also leads to achieving more realistic solutions [ 63 ]. Therefore, the research problem is studied under mixed uncertainty in the present paper.…”

Section: Study Methodologymentioning

confidence: 99%

“…In the above model, represents the importance (weight) of the model robustness, the importance (weight) of the solution robustness, constraints satisfaction levels are shown by , and . To read more about this method, interested readers can see [ 43 , 63 , 64 ]. The RPS counterpart is presented in Supplementary materials (Section A).…”

Section: Study Methodologymentioning

confidence: 99%

“…On the other hand, the main reason for applying the SA, GA, and PSO algorithms is their easy implementation, simple concept, and quick convergence. On the other side, many studies in the field of supply chain applied the mentioned algorithms to solve the research problem (for example, see [ 6 , 21 , 63 , 69 – 71 ]) and achieved the appropriate outputs that showed the good performance of the PSO algorithm to solve the supply chain problem. The methodology of the current study is shown in Fig.…”

Section: Solution Methodologymentioning

confidence: 99%

“…Afterwards, by applying some operators (i.e. crossover and mutation), the solutions are improved [ 63 ]. In this research, the chromosome of the GA is exactly similar to the solution representation of the SA algorithm.…”

Section: Solution Methodologymentioning

confidence: 99%

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An enhanced PSO algorithm to configure a responsive-resilient supply chain network considering environmental issues: a case study of the oxygen concentrator device

Nasrollah

Najafi

Bagherzadeh³

et al. 2022

Neural Comput & Applic

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In recent years, the hyper-competitive marketplace has led to a drastic enhancement in the importance of the supply chain problem. Hence, the attention of managers and researchers has been attracted to one of the most crucial problems in the supply chain management area called the supply chain network design problem. In this regard, this research attempts to design an integrated forward and backward logistics network by proposing a multi-objective mathematical model. The suggested model aims at minimizing the environmental impacts and the costs while maximizing the resilience and responsiveness of the supply chain. Since uncertainty is a major issue in the supply chain problem, the present paper studies the research problem under the mixed uncertainty and utilizes the robust possibilistic stochastic method to cope with the uncertainty. On the other side, since configuring a supply chain is known as an NP-Hard problem, this research develops an enhanced particle swarm optimization algorithm to obtain optimal/near-optimal solutions in a reasonable time. Based on the achieved results, the developed algorithm can obtain high-quality solutions (i.e. solutions with zero or a very small gap from the optimal solution) in a reasonable amount of time. The achieved results demonstrate the negative impact of the enhancement of the demand on environmental damages and the total cost. Also, according to the outputs, by increasing the service level, the total cost and environmental impacts have increased by 41% and 10%, respectively. On the other hand, the results show that increasing the disrupted capacity parameters has led to a 17% increase in the total costs and a 7% increase in carbon emissions. Supplementary Information The online version contains supplementary material available at 10.1007/s00521-022-07739-8.

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Section: Study Methodologymentioning

confidence: 99%

Section: Study Methodologymentioning

confidence: 99%

Section: Solution Methodologymentioning

confidence: 99%

Section: Solution Methodologymentioning

confidence: 99%

See 2 more Smart Citations

An enhanced PSO algorithm to configure a responsive-resilient supply chain network considering environmental issues: a case study of the oxygen concentrator device

Nasrollah

Najafi

Bagherzadeh³

et al. 2022

Neural Comput & Applic

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“…Mokhtarzadeh et al (2021) studied the location-allocation problem by minimizing the costs, noise pollution, and inconvenience caused by the establishment, and developed a combination of clustering and meta-heuristic algorithms to solve it. Nayeri et al (2021) studied a robust fuzzy stochastic model for the responsive-resilient inventory-location problem.…”

Section: Literature Reviewmentioning

confidence: 99%

Optimizing a bi-objective location-allocation-inventory problem in a dual-channel supply chain network with stochastic demands

et al. 2021

Self Cite

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Integrating strategic and tactical decisions to location-allocation and green inventory planning by considering e-commerce features will pave the way for supply chain managers. Therefore, this study provides an effective framework for making decisions related to different levels of the dual-channel supply chain. We provide a bi-objective location-allocation-inventory optimization model to design a dual-channel, multi-level supply chain network. The main objectives of this study are to minimize total cost and environmental impacts while tactical and strategic decisions are integrated. Demand uncertainty is also addressed using stochastic modeling, and inventory procedure is the periodic review . We consider many features in inventory modeling that play a very important role, such as lead time, shortage, inflation, and quality of raw materials, to adapt the model to the real conditions. Since a dual-channel supply chain is becoming more important for sustainable economic development and resource recovery, we combine online and traditional sales channels to design a network. We generate five test problems and solve them by using the augmented ε-constraint method. Also, the Grasshopper optimization algorithm was applied to solve the model in a reasonable time for a large size problem. In order to provide managerial insights and investigate the sensitivity of variables and problem objectives with respect to parameters, sensitivity analysis was performed.

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Supply Chain Resilience: Tactical-Operational Models, a Literature Review

Batista,

Ribeiro,

Barbosa-Póvoa

2023

Springer Proceedings in Mathematics &Amp; Statistics

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A robust fuzzy stochastic model for the responsive-resilient inventory-location problem: comparison of metaheuristic algorithms

Cited by 24 publications

References 55 publications

An enhanced PSO algorithm to configure a responsive-resilient supply chain network considering environmental issues: a case study of the oxygen concentrator device

An enhanced PSO algorithm to configure a responsive-resilient supply chain network considering environmental issues: a case study of the oxygen concentrator device

Optimizing a bi-objective location-allocation-inventory problem in a dual-channel supply chain network with stochastic demands

Supply Chain Resilience: Tactical-Operational Models, a Literature Review

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