A stochastic, two-level optimization model for compressed natural gas infrastructure investments in wastewater management

U-tapao, Chalida; Moryadee, Seksun; Gabriel, Steven A.; Peot, Chris; Ramirez, Mark

doi:10.1016/j.jngse.2015.11.039

Cited by 7 publications

(3 citation statements)

References 3 publications

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“…This approach uses probability distribution functions to describe the uncertainty of supply chain parameters. Aiming at the uncertain factors of supply, demand, production, transportation, and inventory, Xu and Zhou ( 2009 ), Petridis et al ( 2015 ), U-tapao et al ( 2016 ), and Budiman and Rau ( 2019 ) built a multi-objective expected value model, a two-level stochastic optimization model, a probability constraint model, and a mixed integer model, respectively. These scholars also designed the Benders decomposition algorithm, sub-gradient algorithm, and LaGrange dual algorithm, respectively (Lau and Nakandala, 2012 ).…”

Section: Literature Reviewmentioning

confidence: 99%

Robust optimization model of anti-epidemic supply chain under technological innovation: learning from COVID-19

et al. 2022

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The anti-epidemic supply chain plays an important role in the prevention and control of the COVID-19 pandemic. Prior research has focused on studying the facility location, inventory management, and route optimization of the supply chain by using certain parameters and models. Nevertheless, uncertainty, as a vital influence factor, greatly affects the supply chain. As such, the uncertainty that comes with technological innovation has a heightened influence on the supply chain. Few studies have explicitly investigated the influence of technological innovation on the anti-epidemic supply chain under the COVID-19 pandemic. Hence, the current research aims to investigate the influences of the uncertainty caused by technological innovation on the supply chain from demand and supply, shortage penalty, and budget. This paper presents a three-level model of the anti-epidemic supply chain under technological innovation and employs an interval data robust optimization to tackle the uncertainties of the model. The findings are obtained as follows. Firstly, the shortage penalty will increase the costs of the objective function but effectively improve demand satisfaction. Secondly, if the shortage penalty is sufficiently large, the minimum demand satisfaction rate can ensure a fair distribution of materials among the affected areas. Thirdly, technological innovation can reduce costs. The technological innovation related to the transportation costs of the anti-epidemic material distribution center has a greater influence on the optimal value. Meanwhile, the technological innovation related to the transportation costs of the supplier has the least influence. Fourthly, both supply and demand uncertainty can influence costs, but demand uncertainty has a greater influence. Fifthly, the multi-scenario budgeting approach can decrease the calculation complexity. These findings provide theoretical support for anti-epidemic dispatchers to adjust the conservativeness of uncertain parameters under the influence of technological innovation.

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Section: Literature Reviewmentioning

confidence: 99%

Robust optimization model of anti-epidemic supply chain under technological innovation: learning from COVID-19

et al. 2022

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“…The environmental implications linked to solid waste management are growing in urgency mainly in developing countries with poor infrastructure and meager funds allocation for social security and waste management services (Marshall and Farahbakhsh, 2013). The municipal waste management problems have been analyzed and solved by utilizing various tools and techniques all through the past decades (Bertanza et al, 2018; Khan and Samadder, 2014; Romano et al, 2019; Singh, 2019a, 2019b; U-tapao et al, 2016; Yang et al, 2017). Recently, researchers have used various assessment indicators and information and communication technologies (ICTs), such as detection (identification) technology and data possession (acquisition) technology for dealing with the environmental issues of waste disposal (Hannan et al, 2015; Olay-Romero et al, 2020).…”

Section: Rationalementioning

confidence: 99%

Indicators and ICTs application for municipal waste management

Singh

2021

Waste Manag Res

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The worldwide populace is rising steadily. Urbanization is likewise expanding quickly with the rising populace. Fast urbanization has considerably increased the generation of municipal solid waste (MSW). The MSW management issues have recently been analyzed through various assessment indicators and information and communication technologies (ICTs). This article provides an overview of applications of assessment indicators and ICTs for addressing the environmental issues of waste disposal and management in municipalities. The selection of indicators mainly depends on the stakeholders’ specific requirements, such as waste management strategies, urban planning and development, human health, and energy generation. The literature analysis revealed that collection, sorting, recycling, cost efficiency, and environmental aspect were the leading indicators used in waste management studies. And these indicators reduce the complexity of systems and formulate evaluations easier for the decision-maker. Moreover, these are also helpful in assessing the improvement and reporting the waste condition to the expert. These analysis further revealed that information and communication technology is a requirement in the planning and managing of current solid waste disposal problems. The use of ICTs in waste management systems mitigates possible constraints regarding spot selection, inept waste disposal, waste collection monitoring, and proper recycling.

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“…The non-cooperative game theoretical complementarity model is developed in the general algebraic modeling system (GAMS) as a mixed complementarity problem (MCP) (Rosenthal 2004). Gabriel et al (2001), Hobbs (2001) and Tung et al (2013) have proved the mathematical properties of existence and uniqueness for the MCP solution. In this paper, the MCP problem is solved using the PATH solver.…”

Section: Toolsmentioning

confidence: 99%

Study of the impacts of upstream natural gas market reform in China on infrastructure deployment and social welfare using an SVM-based rolling horizon stochastic game analysis

Wang

McLellan

et al. 2018

Pet. Sci.

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Natural gas is expected to play a much more important role in China in future decades, and market reform is crucial for its rapid market penetration. At present, the main gas fields, pipelines and liquefied natural gas (LNG) infrastructure are mainly monopolized by large state-owned companies, and one of the important market reform policies is to open up LNG import rights to smaller private companies and traders. Therefore, in the present study, a game theoretical model is proposed to analyze and compare the impacts of different market structures on infrastructure deployment and social welfare. Moreover, a support vector machine-based rolling horizon stochastic method is adopted in the model to simulate real LNG price fluctuations. Four market reform scenarios are proposed considering different policies such as business separation, third-party access (TPA) and their combinations. The results indicate that, with third-party access (TPA) entrance into the LNG market, the construction of LNG infrastructure will be promoted and more gas will be provided at lower prices, and thus the total social welfare will be improved greatly.Keywords LNG market reform Á Market structure Á Third-party access Á Rolling horizon stochastic method Á Game theory Abbreviations DP Domestic gas field producer LI Original LNG importer LT Subsequent LNG trader

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A stochastic, two-level optimization model for compressed natural gas infrastructure investments in wastewater management

Cited by 7 publications

References 3 publications

Robust optimization model of anti-epidemic supply chain under technological innovation: learning from COVID-19

Robust optimization model of anti-epidemic supply chain under technological innovation: learning from COVID-19

Indicators and ICTs application for municipal waste management

Study of the impacts of upstream natural gas market reform in China on infrastructure deployment and social welfare using an SVM-based rolling horizon stochastic game analysis

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