Dynamic optimization of emergency resource scheduling in a large-scale maritime oil spill accident

Zhang, Lingye; Lu, Jing; Yang, Zaili

doi:10.1016/j.cie.2020.107028

Cited by 21 publications

(7 citation statements)

References 47 publications

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“…Among the articles in this field selected for this study, Refs. [112][113][114][115][116][117][118] applied uncertainty method based on uncertainty theory. For example, Li et al [112] employed uncertainty planning methods to deal with the medical material dispatching problem in emergency events.…”

Section: Distribution Papers Based On Emergency Network Optimizationmentioning

confidence: 99%

Uncertainty Analysis and Optimization Modeling with Application to Supply Chain Management: A Systematic Review

et al. 2023

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In recent years, there have been frequent cases of impact on the stable development of supply chain economy caused by uncertain events such as COVID-19 and extreme weather events. The creation, management, and impact coping techniques of the supply chain economy now face wholly novel requirements as a result of the escalating level of global uncertainty. Although a significant literature applies uncertainty analysis and optimization modeling (UAO) to study supply chain management (SCM) under uncertainty, there is a lack of systematic literature review and research classification. Therefore, in this paper, 121 articles published in 44 international academic journals between 2015 and 2022 are extracted from the Web of Science database and reviewed using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA). Bibliometric analysis and CiteSpace software are used to identify current developments in the field and to summarize research characteristics and hot topics. The selected published articles are classified and analyzed by author name, year of publication, application area, country, research purposes, modeling methods, research gaps and contributions, research results, and journals to comprehensively review and evaluate the SCM in the application of UAO. We find that UAO is widely used in SCM under uncertainty, especially in the field of decision-making, where it is common practice to abstractly model the decision problem to obtain scientific decision results. This study hopes to provide an important and valuable reference for future research on SCM under uncertainty. Future research could combine uncertainty theory with supply chain management segments (e.g., emergency management, resilience management, and security management), behavioral factors, big data technologies, artificial intelligence, etc.

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Section: Distribution Papers Based On Emergency Network Optimizationmentioning

confidence: 99%

Uncertainty Analysis and Optimization Modeling with Application to Supply Chain Management: A Systematic Review

et al. 2023

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“…Shen et al [29] proposed a triangular fuzzy function to obtain the fuzzy demand considering the uncertainty of the demand in the disaster area, constructed a multi-objective model considering the carbon emissions, and used a two-stage hybrid algorithm to solve the problem. Zhang et al [30] proposed a novel dynamic multi-objective split-delivery location-routing two-stage optimization model for the emergency logistics of offshore oil spill accidents, and developed a hybrid heuristic algorithm to solve it. Ghasemi et al [31] proposed a scenario-based stochastic multi-objective location-allocation-routing model considering the existence of uncertainty before and after a disaster, which was solved using epsilon constraints and meta-heuristic algorithms.…”

Section: Literature Reviewmentioning

confidence: 99%

Robust Bi-Level Optimization for Maritime Emergency Materials Distribution in Uncertain Decision-Making Environments

Wang,

Peng,

2023

Mathematics

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Maritime emergency materials distribution is a key aspect of maritime emergency responses. To effectively deal with the challenges brought by the uncertainty of the maritime transport environment, the multi-agent joint decision-making location-routing problem of maritime emergency materials distribution (MEMD-LRP) under an uncertain decision-making environment is studied. First, two robust bi-level optimization models of MEMD-LRP are constructed based on the effect of the uncertainty of the ship’s sailing time and demand of emergency materials at the accident point, respectively, on the premise of considering the rescue time window and priority of emergency materials distribution. Secondly, with the help of robust optimization theory and duality theory, the robust optimization models are transformed into robust equivalent models that are easy to solve. Finally, a hybrid algorithm based on the ant colony and tabu search (ACO-TS) algorithm solves multiple sets of numerical cases based on the case design of the Bohai Sea area, and analyzes the influence of uncertain parameters on the decision making of MEMD-LRP. The study of MEMD-LRP under uncertain decision-making environments using bi-level programming and robust optimization methods can help decision makers at different levels of the maritime emergency logistics system formulate emergency material reserve locations and emergency material distribution schemes that can effectively deal with the uncertainty in maritime emergencies.

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“…Currently, existing research focuses on the location of the emergency supplies reserve base, rescue resource allocation, and configuration optimization of salvage vessels [91,115]. Moreover, most research has taken oil spills as a case to analyze emergency resource dispatching [92,116]. Notably, in the future, comparative analyses of the application effects under different emergency scenario levels will be important for improving the efficiency of maritime emergency salvage.…”

Section: Scenario Representation and Digital Twins Are Becoming Criti...mentioning

confidence: 99%

A Systematic Literature Review of Maritime Transportation Safety Management

Xu,

Ma,

Zhao

et al. 2023

JMSE

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Maritime transportation plays a critical role in global trade, and studies on maritime transportation safety management are of great significance to the sustainable development of the maritime industry. Consequently, there has been an increasing trend recently in studies on maritime transportation safety management, especially in terms of safety risk analysis and emergency management. Therefore, the general idea of this article is to provide a detailed literature review of maritime transportation safety management based on 186 articles in the Web of Science (WOS) database published from 2011 to 2022. The purposes of this article are as follows: (1) to provide a statistics-based description and conduct a network-based bibliometric analysis on the basis of the collected articles; (2) to summarize the methodologies/technologies employed in maritime transportation safety management spatiotemporally; and (3) to propose four potential research perspectives in terms of maritime transportation safety management. Based on the findings and insights obtained from the bibliometric and systematic review, the development of a resilient maritime transportation system could be facilitated by means of data- or intelligence-driven technologies, such as scenario representation, digital twinning, and data simulation. In addition, the issues facing intelligent maritime shipping greatly challenge the current maritime safety management system due to the co-existence of intelligent and non-intelligent maritime operation.

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Dynamic optimization of emergency resource scheduling in a large-scale maritime oil spill accident

Cited by 21 publications

References 47 publications

Uncertainty Analysis and Optimization Modeling with Application to Supply Chain Management: A Systematic Review

Uncertainty Analysis and Optimization Modeling with Application to Supply Chain Management: A Systematic Review

Robust Bi-Level Optimization for Maritime Emergency Materials Distribution in Uncertain Decision-Making Environments

A Systematic Literature Review of Maritime Transportation Safety Management

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