A resource allocation framework for predisaster resilience management of interdependent infrastructure networks

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Jingran Sun ◽  
Srijith Balakrishnan ◽  
Zhanmin Zhang
Keyword(s):  
Resource Allocation ◽  
Extreme Events ◽  
Asset Management ◽  
Agent Based Modeling ◽  
Methodological Framework ◽  
Content Type ◽  
Agent Based ◽  
Allocation Process ◽  
Infrastructure Network ◽  
Resource Allocation Process

PurposeResource allocation is essential to infrastructure management. The purpose of this study is to develop a methodological framework for resource allocation that takes interdependencies among infrastructure systems into consideration to minimize the overall impact of infrastructure network disruptions due to extreme events.Design/methodology/approachTaking advantage of agent-based modeling techniques, the proposed methodology estimates the interdependent effects of a given infrastructure failure which are then used to optimize resource allocation such that the network-level resilience is maximized.FindingsThe findings of the study show that allocating resources with the proposed methodology, where optimal infrastructure reinforcement interventions are implemented, can improve the resilience of infrastructure networks with respect to both direct and interdependent risks of extreme events. These findings are also verified by the results of two case studies.Practical implicationsAs the two case studies have shown, the proposed methodological framework can be applied to the resource allocation process in asset management practices.Social implicationsThe proposed methodology improves the resilience of the infrastructure network, which can alleviate the social and economic impact of extreme events on communities.Originality/valueCapitalizing on the combination of agent-based modeling and simulation-based optimization techniques, this study fulfills a critical gap in infrastructure asset management by incorporating infrastructure interdependence and resilience concepts into the resource allocation process.

Assessment of Resource Allocation and Tradeoff Analysis Approaches in Transportation Asset Management

2018 ◽  
Vol 2672 (44) ◽  
pp. 21-31 ◽  
Author(s):  
James Bryce ◽  
Gonzalo Rada ◽  
Samuel Van Hecke ◽  
Joseph Zissman
Keyword(s):  
Resource Allocation ◽  
Asset Management ◽  
State Agencies ◽  
Multi Objective ◽  
Current State ◽  
Allocation Process ◽  
Transportation Asset Management ◽  
Key Steps ◽  
Transportation Agencies ◽  
Resource Allocation Process

Transportation asset management (TAM) practices continue to grow and to develop as transportation agencies seek to make more objective and defensible decisions, as well as responding to recent legislation. One primary goal of TAM is to provide a structure in which decisions on how to distribute resources across many disparate assets can be made using a systematic process. Resource allocation is analogous to multi-objective optimization, and thus presents the complication that many potential optimal solutions (i.e., a Pareto set) can be found. To solve the multi-objective resource allocation problem, many approaches have been recommended, such as the use of utility theory and weighting functions to express preferences that result in a single solution being selected. This paper discusses those recommendations, as well as describing the current state of the resource allocation process in an effort to identify gaps in practice and, in turn, to provide recommendations for addressing those gaps. First, the process of cross-asset resource allocation is deconstructed to highlight the key steps. Then, current practices identified from the literature, as well as from interviews with five State agencies are discussed. Finally, a set of recommendations for improving resource allocation and the supporting processes within resource allocation are presented.

scholarly journals Agent-Based Modeling Demonstrates How Local Chemotactic Behavior Can Shape Biofilm Architecture

mSphere ◽  
2019 ◽  
Vol 4 (3) ◽  
Author(s):  
Emily G. Sweeney ◽  
Andrew Nishida ◽  
Alexandra Weston ◽  
Maria S. Bañuelos ◽  
Kristin Potter ◽  
...  
Keyword(s):  
Helicobacter Pylori ◽  
Three Dimensional ◽  
Structural Features ◽  
Agent Based Modeling ◽  
Emergent Properties ◽  
Cellular Interactions ◽  
Biofilm Growth ◽  
Content Type ◽  
Agent Based ◽  
H Pylori

ABSTRACTBacteria are often found living in aggregated multicellular communities known as biofilms. Biofilms are three-dimensional structures that confer distinct physical and biological properties to the collective of cells living within them. We used agent-based modeling to explore whether local cellular interactions were sufficient to give rise to global structural features of biofilms. Specifically, we asked whether chemorepulsion from a self-produced quorum-sensing molecule, autoinducer-2 (AI-2), was sufficient to recapitulate biofilm growth and cellular organization observed for biofilms ofHelicobacter pylori, a common bacterial resident of human stomachs. To carry out this modeling, we modified an existing platform, Individual-based Dynamics of Microbial Communities Simulator (iDynoMiCS), to incorporate three-dimensional chemotaxis, planktonic cells that could join or leave the biofilm structure, and cellular production of AI-2. We simulated biofilm growth of previously characterizedH. pyloristrains with various AI-2 production and sensing capacities. Using biologically plausible parameters, we were able to recapitulate both the variation in biofilm mass and cellular distributions observed with these strains. Specifically, the strains that were competent to chemotax away from AI-2 produced smaller and more heterogeneously spaced biofilms, whereas the AI-2 chemotaxis-defective strains produced larger and more homogeneously spaced biofilms. The model also provided new insights into the cellular demographics contributing to the biofilm patterning of each strain. Our analysis supports the idea that cellular interactions at small spatial and temporal scales are sufficient to give rise to larger-scale emergent properties of biofilms.IMPORTANCEMost bacteria exist in aggregated, three-dimensional structures called biofilms. Although biofilms play important ecological roles in natural and engineered settings, they can also pose societal problems, for example, when they grow in plumbing systems or on medical implants. Understanding the processes that promote the growth and disassembly of biofilms could lead to better strategies to manage these structures. We had previously shown thatHelicobacter pyloribacteria are repulsed by high concentrations of a self-produced molecule, AI-2, and thatH. pylorimutants deficient in AI-2 sensing form larger and more homogeneously spaced biofilms. Here, we used computer simulations of biofilm formation to show that localH. pyloribehavior of repulsion from high AI-2 could explain the overall architecture ofH. pyloribiofilms. Our findings demonstrate that it is possible to change global biofilm organization by manipulating local cell behaviors, which suggests that simple strategies targeting cells at local scales could be useful for controlling biofilms in industrial and medical settings.

scholarly journals Recommendation with Diversity: Mass Diffusion Model Based on Trust Network and Object Reputation

2021 ◽  
Vol 2021 ◽  
pp. 1-13
Author(s):  
Yun Bai ◽  
Wandong Cai
Keyword(s):  
Resource Allocation ◽  
Diffusion Model ◽  
Recommendation System ◽  
Small Degree ◽  
Mass Diffusion ◽  
Recommendation Algorithm ◽  
Trust Relationship ◽  
Positive Effects ◽  
Allocation Process ◽  
Resource Allocation Process

The traditional mass diffusion recommendation algorithm only relies on the user’s object collection relationship, resulting in poor recommendation performance for users with small purchases (i.e., small-degree user), and it is difficult to balance the accuracy and diversity of the recommendation system. This paper introduces the trust relationship into the resource allocation process of the traditional mass diffusion algorithm and proposes the Dual Wing Mass Diffusion model (DWMD), which constructs a dual wing graph based on trust relationships and object collection relationships. Implicit trust is mined according to the network structure of the trust relationship and integrated into the resource allocation process, and then merging the positive effects of object reputation on a recommendation through tunable scaling parameters. The user controls the tunable scaling parameter to achieve the best recommendation performance. The experimental results show that the DWMD method significantly improves diversity and novelty while ensuring high accuracy and effectively improves the accuracy and diversity balance. The improved recommendation performance for small-degree users proves that the trust relationship can effectively alleviate the generalized cold start problem of the recommendation algorithm for users who collect a small number of objects.

Use of a sonification system for science learning by people who are blind

2016 ◽  
Vol 10 (4) ◽  
pp. 187-198 ◽  
Author(s):  
Orly Lahav ◽  
Nuha Chagab ◽  
Vadim Talis
Keyword(s):  
Complex Systems ◽  
Conceptual Knowledge ◽  
Science Curriculum ◽  
Low Cost ◽  
Agent Based Modeling ◽  
Learning System ◽  
Learning Ability ◽  
Content Type ◽  
Agent Based ◽  
K 12

Purpose The purpose of this paper is to examine a central need of students who are blind: the ability to access science curriculum content. Design/methodology/approach Agent-based modeling is a relatively new computational modeling paradigm that models complex dynamic systems. NetLogo is a widely used agent-based modeling language that enables exploration and construction of models of complex systems by programming and running the rules and behaviors. Sonification of variables and events in an agent-based NetLogo computer model of gas in a container is used to convey phenomena information. This study examined mainly two research topics: the scientific conceptual knowledge and systems reasoning that were learned as a result of interaction with the listen-to-complexity (L2C) environment as appeared in answers to the pre- and post-tests and the learning topics of kinetic molecular theory of gas in chemistry that was learned as a result of interaction with the L2C environment. The case study research focused on A., a woman who is adventitiously blind, for eight sessions. Findings The participant successfully completed all curricular assignments; her scientific conceptual knowledge and systems reasoning became more specific and aligned with scientific knowledge. Practical implications A practical implication of further studies is that they are likely to have an impact on the accessibility of learning materials, especially in science education for students who are blind, as equal access to low-cost learning environments that are equivalent to those used by sighted users would support their inclusion in the K-12 academic curriculum. Originality/value The innovative and low-cost learning system that is used in this research is based on transmittal of visual information of dynamic and complex systems, providing perceptual compensation by harnessing auditory feedback. For the first time the L2C system is based on sound that represents a dynamic rather than a static array. In this study, the authors explore how a combination of several auditory representations may affect cognitive learning ability.

The Resource Allocation Process

2018 ◽  
pp. 79-93
Author(s):  
Richard Busulwa ◽  
Matthew Tice ◽  
Bruce Gurd
Keyword(s):  
Resource Allocation ◽  
Allocation Process ◽  
Resource Allocation Process

A Stochastic Decentralized Resource Allocation Process: Part II

Econometrica ◽  
1975 ◽  
Vol 43 (3) ◽  
pp. 363 ◽  
Author(s):  
Leonid Hurwicz ◽  
Roy Radner ◽  
Stanley Reiter
Keyword(s):  
Resource Allocation ◽  
Allocation Process ◽  
Decentralized Resource Allocation ◽  
Resource Allocation Process

Facilitating organizational learning through agent-based modeling and simulation experimentation

2016 ◽  
Vol 23 (6) ◽  
pp. 429-443 ◽  
Author(s):  
Saša Baškarada ◽  
Arvind Chandran ◽  
Mina Shokr ◽  
Christopher Stewart
Keyword(s):  
Organizational Learning ◽  
Modeling And Simulation ◽  
Agent Based Modeling ◽  
Knowledge Generation ◽  
Generation Process ◽  
Complex Environments ◽  
Content Type ◽  
Agent Based ◽  
Internal Knowledge

Purpose In addition to requiring high absorptive capacity, contemporary organizations operating in highly dynamic and complex environments also require the ability to create knowledge internally, within the organization. While the organizational learning (OL) literature has produced a plethora of theories and frameworks, there has been relatively little empirical research on specific mechanisms for internal knowledge generation. Accordingly, this paper aims to answer calls for more research on mechanisms for internal generation of organizational knowledge. Design/methodology/approach This paper is an in-depth case study in the Australian Defence Organisation (ADO). Findings The paper presents a cyclical eight-stage knowledge generation process and demonstrates how agent-based modeling and simulation (ABMS) may be used to facilitate OL. Originality/value By detailing an in-depth case study of an ABMS mechanism for internal knowledge generation in the ADO, this paper provides a novel and relevant contribution to the OL literature.

Research on Multi-Project Resource Allocation Process and Application

2013 ◽  
Vol 357-360 ◽  
pp. 2267-2272
Author(s):  
Xin Li Zhang ◽  
Jie Li ◽  
Yan Fang Zhu
Keyword(s):  
Resource Allocation ◽  
Allocation Problem ◽  
Resource Allocation Problem ◽  
Interactive Process ◽  
Allocation Process ◽  
Fixed Period ◽  
Resource Allocation Process

Based on the existing research on multi-project resource allocation, this research presents the triangle relationship diagram about the objective, constraints, and algorithm during project resource allocation; and designs the interactive process for multi-project resource allocation, which combines the project objective, constraint, and algorithm. In addition, a case about fixed period - fixed resources problem is solved to verify the feasibility of the interactive process; the research develops the comprehensive concept for project resource allocation problem.

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