Managing congestion in a multi-modal transportation network under biomass supply uncertainty

Poudel, Sushil; Quddus, Abdul; Marufuzzaman, Mohammad; Bian, Linkan; Burch, Reuben F.

doi:10.1007/s10479-017-2499-y

Cited by 16 publications

(4 citation statements)

References 59 publications

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“…Hamdan and Diabat ( 2019 ) considered production, inventory, and location decisions using a TSP model for a blood SCN design. Poudel et al ( 2019 ) designed a biomass SCN with regard to uncertain feedstock supply using a TSP model. Tosarkani and Amin ( 2019 ) designed a lead-acid battery CLSCN considering the environmental compliance of involved facilities.…”

Section: Literature Reviewmentioning

confidence: 99%

Design and optimization of a sustainable and resilient mask supply chain during the COVID-19 pandemic: A multi-objective approach

Alizadeh-Meghrazi

Tosarkani

Amin

et al. 2022

Environ Dev Sustain

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Wearing a mask or a face covering became mandatory in indoor public spaces to reduce the spread of coronavirus disease 2019 (COVID-19). The Ontario government (i.e., a province of Canada) encouraged medical supply producers to switch their operations to produce personal protective equipment (e.g., masks) during the COVID-19 pandemic. In this regard, there are several uncertain parameters (e.g., operational costs, market demand, and capacity levels of facilities) affecting the performance of producers in a medical supplies market. In this study, we propose a flexible optimization model to configure a robust mask supply chain network under uncertainty. Furthermore, companies are supposed to undertake their operations based on sustainable manners, in compliance with provincial policy, in Ontario. Therefore, the proposed flexible optimization model is extended to a robust multi-objective model to investigate sustainable strategies in a mask supply chain network design problem. The applicability of this model is demonstrated for the Greater Toronto Area, Canada.

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Section: Literature Reviewmentioning

confidence: 99%

Design and optimization of a sustainable and resilient mask supply chain during the COVID-19 pandemic: A multi-objective approach

Alizadeh-Meghrazi

Tosarkani

Amin

et al. 2022

Environ Dev Sustain

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“…Darestani and Hemmati (2019) optimized a robust bi-objective CLSC network for perishable goods considering a queue system. Poudel et al (2019) managed congestion in a multi-modal transportation network under biomass supply uncertainty.…”

Section: Literature Reviewmentioning

confidence: 99%

Solving a new bi-objective multi-echelon supply chain problem with a Jackson open-network issue under uncertainty

2021

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In today's world, changes in the economic and industrial sectors are taking place more quickly than in the past. Based on today's competitive market, considering the needs and desires of the customer is very important. Thus, designing the supply chain network to minimize the costs and improve the system efficiency, the service facility, and attention to the timely service delivery to the customer should be considered. Also, deployment costs to determine the number and position of facilities are regarded as another strategic issue. Therefore, to become closer to the real-world application, by considering the Jackson network model (queuing theory), the present study aims to design a closedloop supply chain (CLSC) network to reduce the waiting time in the queue. Two objectives, namely minimizing the cost and waiting time incurred in queues formed in producers and distributors, are investigated. Queuing mathematical expressions are used both in dealing with objectives and constraints. To develop a model, which is close to real by considering uncertainty, the parameters, including demand rate and shipping cost of products, were considered as a trapezoidal fuzzy number. Also, we crisp this fuzzy uncertainty using both Jimenez and chance-constrained programming approaches. Due to the suggested model's complexity and nonlinearity, we linearized the mathematical model as much as possible, then two meta-heuristic algorithms, namely multiobjective particle swarm optimization (MOPSO) and non-dominated sorted genetic algorithm (NSGA-II), are used to solve the model. First, the structural parameters of these algorithms are tuned by the Taguchi method. Then, numerous numerical test problems ranging from small to large scales are used to compare these algorithms considering Pareto front measuring indexes and various hypothesis tests.

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“…We used existing multi-modal and inter-modal facilities as potential multi-modal facilities. The potential biorefinery locations are selected based on the prior literatures applied to our test region ( [37,38]). Figure 3b shows the locations and distribution of potential multi-modal facilities and biorefineries in this region.…”

Section: Data Descriptionmentioning

confidence: 99%

“…Please note that the biofuel supply chain system from biomass production to bio-refineries can be viewed as a hub-and-spoke transportation network. Please note that most of the prior studies (e.g., [34][35][36][37][38][39][40]) assume that the transportation hubs are always functioning and will never fail, which cannot adequately describe the real-world scenarios. A few studies focus on managing and rescheduling rail and port operations during different disrupted scenarios (e.g., [41][42][43]).…”

Section: Introductionmentioning

confidence: 99%

Designing a Reliable and Congested Multi-Modal Facility Location Problem for Biofuel Supply Chain Network

et al. 2018

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This study presents a mathematical model that designs a reliable multi-modal transportation network for a biofuel supply chain system while site-dependent facility failure and congestion are taken into consideration. The proposed model locates the multi-modal facilities and biorefineries and determines the optimal production, storage, and routing plans in such a way that the overall system cost is minimized. We propose a hybrid Constraint generation-based Rolling horizon algorithm to solve this challenging N P-hard problem. The performance of this algorithm is tested in a example case study with numerical analysis showing that the hybrid algorithm can find near-optimal solutions to large-scale problem instances in a reasonable amount of time. Results indicate that the effect of congestion reduces the usage of multi-modal facilities in the biofuel supply chain network while bio-refineries and multi-modal facilities tend to move away from coastal areas when disruption probabilities are taken into consideration.

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Managing congestion in a multi-modal transportation network under biomass supply uncertainty

Cited by 16 publications

References 59 publications

Design and optimization of a sustainable and resilient mask supply chain during the COVID-19 pandemic: A multi-objective approach

Design and optimization of a sustainable and resilient mask supply chain during the COVID-19 pandemic: A multi-objective approach

Solving a new bi-objective multi-echelon supply chain problem with a Jackson open-network issue under uncertainty

Designing a Reliable and Congested Multi-Modal Facility Location Problem for Biofuel Supply Chain Network

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