A two-stage resource allocation model for lifeline systems quick response with vulnerability analysis

Zhang, C.; Xiao, Liu; Jiang, Yiping; Fan, Bo; Song, Xiang

doi:10.1016/j.ejor.2015.10.022

Cited by 28 publications

(20 citation statements)

References 34 publications

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“…Besides, heterogeneity and eligibility restrictions of EOs, sequences and urgencies of ETs, as well as sustainability are all considered by comparing with all literature presented in Table 1. (4) Single objective model for EOA is favored in literature except for Su et al [22], Zhang et al [23], Zheng et al [24,25]. Moreover, time or similar is the most popular objective, and cost is the secondary, carbon emissions are rare.…”

Section: Objmentioning

confidence: 99%

“…In this paper, their insights are leveraged and extended to develop a linear weighted method to integrate two objective functions into a single one. Consequently, the objective functions can be replaced by the following Formula (23).…”

Section: Handling Strategies For Multiple Objectivesmentioning

confidence: 99%

“…Su et al [22] considered matching problem between multiple rescue teams and concurrent incidents, thus obtaining the optimal scheme concerning rescue teams. To restore the critical components of multiple interdependent lifeline infrastructure systems, Zhang et al [23] focused on homogeneous rescue team allocation problem with the concern of a precedence relation constraint so as to reduce the total losses and improve the efficiency of disaster response. Only assignment of EO is considered in the aforementioned literature.…”

Section: Literature Reviewmentioning

confidence: 99%

“…With respect to EOA problem, Su et al [22] formulated rescue teams allocation as an integer programming model to minimize the weighted travel time and total emergency costs. Zhang et al [23] developed a two-stage stochastic mixed-integer programming model for rescue team allocation with the minimization of total losses or costs and the latest completion time of tasks (namely, makespan). Zheng et al [25] focused on matching problem between rescue teams and tasks, aiming to minimize the weighted completion time and total operation risk.…”

Section: Literature Reviewmentioning

confidence: 99%

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Multi-Objective Optimization Model of Emergency Organization Allocation for Sustainable Disaster Supply Chain

Cao

Qin

et al. 2017

Sustainability

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Abstract:To mitigate or reduce various losses and improve efficiency of disaster response, the focus of this paper is to design optimized strategies of emergency organization allocation regarding sustainability. Firstly, an integrated framework including several elements such as emergency organization, task, decision-agents, environment and their relations is developed from a systematic perspective. Then, this problem is formulated as a novel multi-objective 0-1 integer programming model to minimize total weighted completion times, total carbon emissions and total emergency costs. Next, branch and bound approach and handling strategies for multiple objectives are designed to solve this model. Finally, a case study from the Wenchuan earthquake is presented to illustrate the proposed model and solution strategies. Computational results demonstrate their significant potential advantages on allocating emergency organization from the perspectives of best practice, objective functions, preferences of decision-agents, and problem size.

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Section: Objmentioning

confidence: 99%

Section: Handling Strategies For Multiple Objectivesmentioning

confidence: 99%

Section: Literature Reviewmentioning

confidence: 99%

Section: Literature Reviewmentioning

confidence: 99%

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Multi-Objective Optimization Model of Emergency Organization Allocation for Sustainable Disaster Supply Chain

Cao

Qin

et al. 2017

Sustainability

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“…A cooperative co-evolutionary multi-objective algorithm was designed to produce high-quality solutions (Xiong et al, 2016). Zhang et al (2016) divided RA problems into two stages in which the first stage was to minimize the total losses, while the second optimized RA problems by using the proposed heuristic algorithm in the polynomial complexity. Equally, a compromise programming method was employed to trade off the economic benefit efficiency and equity in the water allocation problems (Hu et al, 2016).…”

Section: Introductionmentioning

confidence: 99%

Limited public resources allocation model based on social fairness using an extended VIKOR method

Jiang

2016

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Article information:To cite this document: Wenqi Jiang, (2016) "Limited public resources allocation model based on social fairness using an extended VIKOR method", Kybernetes, Vol. 45 Issue: 7, pp.998-1012, https For AuthorsIf you would like to write for this, or any other Emerald publication, then please use our Emerald for Authors service information about how to choose which publication to write for and submission guidelines are available for all. Please visit www.emeraldinsight.com/authors for more information. About Emerald www.emeraldinsight.comEmerald is a global publisher linking research and practice to the benefit of society. The company manages a portfolio of more than 290 journals and over 2,350 books and book series volumes, as well as providing an extensive range of online products and additional customer resources and services.Emerald is both COUNTER 4 and TRANSFER compliant. The organization is a partner of the Committee on Publication Ethics (COPE) and also works with Portico and the LOCKSS initiative for digital archive preservation.*Related content and download information correct at time of download. Limited public resources allocation model based on social fairness using an extended VIKOR method Wenqi JiangNanjing University of Science and Technology, Nanjing, China Abstract Purpose -Different from manufacturing resources allocation problems, the prices and amounts of limited public service resources could not be changed with the consumers' requirements and social fairness is the most important objective for improving allocation efficiency. To measure social fairness reasonably, the purpose of this paper is fourfold: first, divide social fairness into longitudinal comparative fairness and crosswise comparative fairness, therefore providing their calculation formula and describing the comprehensive fair degree by using the interval numbers. Second, the comparison regulations of interval numbers are given and the corresponding features are also described. Third, an extension of VIKOR method is put forward for evaluating social fairness of different allocation alternatives with interval numbers. Finally, a numerical example illustrates the proposed method and clarifies the main results developed in the paper. Design/methodology/approach -In this paper, the author depicts the social fair degree as an interval number, and thus proposes the comparison method between any two interval numbers. Based on the basis procedure of the VIKOR method, the paper proposes an extension of the fuzzy VIKOR method with the interval numbers to rank and select the compromise allocation alternatives. Finally, a numerical example illustrates the practicability of the proposed method.Findings -The comparison of interval numbers is very important when the author evaluates the decision alternatives. Through analyzing the present comparison methods, the paper proposes the simple method of comparing the interval numbers, which can obtain the same results with the above two methods. The fuzzy VIKOR method, a popular multi-...

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A heuristic-based simulated annealing algorithm for the scheduling of relief teams in natural disasters

et al. 2021

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A two-stage resource allocation model for lifeline systems quick response with vulnerability analysis

Cited by 28 publications

References 34 publications

Multi-Objective Optimization Model of Emergency Organization Allocation for Sustainable Disaster Supply Chain

Multi-Objective Optimization Model of Emergency Organization Allocation for Sustainable Disaster Supply Chain

Limited public resources allocation model based on social fairness using an extended VIKOR method

A heuristic-based simulated annealing algorithm for the scheduling of relief teams in natural disasters

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