Computational GIS and Agent-Based Model Development for Routing Optimization to Facilitate Pavement Condition Data Collection

Author(s):  
Natalia M. Sanabria ◽  
Elmira Kalhor ◽  
Vanessa Valentin ◽  
Susan M. Bogus ◽  
Guohui Zhang
Author(s):  
Caroline C Krejci

Purpose – The purpose of this paper is to present a conceptual framework for a hybrid simulation model that can be used to study the decision making and behaviors of humanitarian logistics actors to determine how/whether certain coordination mechanisms enable better relief chain efficiency and effectiveness over time. Design/methodology/approach – The agent-based portion of the model is used to represent human decision making and interactions in a more realistic way than has been done previously, and the discrete-event simulation (DES) portion of the model allows the movement of vehicles, materials, and information throughout a supply network to be represented in a way that allows for dynamic and stochastic behavior. Findings – Coordinated efforts by actors in humanitarian logistics operations involve complex interactions and adaptations over time, which can be capture and explored via hybrid agent-based model (ABM)-DES modeling. Research limitations/implications – This paper describes a framework for a hybrid ABM-DES model. The actual development and implementation of the model, including input data collection and analysis, model development, experimentation, and output data collection and analysis, will be the subject of future work. Practical implications – The hybrid model framework provides other researchers with a starting point for model development. Social implications – This paper provides a basis for future modeling and assessment of coordination in humanitarian logistics, an area that is in need of research. Originality/value – The hybrid simulation modeling framework presented in this paper is a novel application of a new modeling methodology to the problem of coordination in humanitarian logistics.


2021 ◽  
Author(s):  
Behshad Mohajer ◽  
David Yu ◽  
Marco Janssen ◽  
Margaret Garcia

<p>Hydrological systems in the Anthropocene have shown substantial shifts from their natural processes due to human modifications. Consequently, deploying coupled human-water modeling is a critical tool to analyze observed changes. However, the development of socio-hydrological models often requires extensive qualitative data collection in the field and analysis. Despite the advances in developing inter-disciplinary methodologies in utilizing qualitative data for coupled human-water modeling, there is a need to identify influential parameters in these systems to inform data collection. Here, we present an exploratory socio-hydrological model to systemically investigate the feedback system of public infrastructure providers, resource users, and the dynamics of water scarcity at the catchment scale to inform data collection and analysis in the field. Specifically, we propose a novel socio-hydrological model by employing and integrating a top-down hydrological model and an extension of Aqua.MORE Model (an Agent-Based Model designed to simulate dynamics of water supply and demand). Specifically, we model alternate behavioral theories of human decision-making to represent the agents’ behavior. Then, we perform sensitivity analysis techniques to identify key socio-economic and behavioral parameters affecting emergence patterns in a stylized human-dominated catchment. We apply the proposed methodology to the Lake Mendocino Watershed in Northern California, US. The results will potentially point which parameters are influential and how they could be mapped to a particular interview or survey question. This study will help us to identify features of decision-making behavior for inclusion in fieldwork, that be might be overlooked in the absence of the proposed modeling. We anticipate that the proposed approach also contributes to the current Panta Rhei Research Initiative of the International Association of Hydrological Sciences (IAHS) which aims at improving the interpretation of the hydrological processes governing the socio-hydrological systems by focusing on their changing dynamics in connection with rapidly changing human systems.</p>


2020 ◽  
Vol 21 (3) ◽  
pp. 158-174
Author(s):  
G. B. Korovin

The study of the transformation of the industrial complex and industrial products markets, due to its complexity, involves the use of tools that can adequately simulate elaborate systems of interconnections. The paper aims at developing an agent-based model of digital transformation of the regional industrial complex. The research methodology relies on regional economics, game and contract theories, the network approach, as well as the concepts of new industrialisation and the fourth industrial revolution. The author uses simulation modelling to study the individual behaviour of agents. As one of its outcomes, the article provides a methodological rationale for modelling industrial development processes by simulating the behaviour of interacting agents. The structural elements of the proposed model include an interaction environment, four classes of agents with individual parameters, strategies and rules of behaviour, a complex of external stimulating factors and a set of indicators of a phased digital transformation of an industrial complex. The model development algorithm consists of three parts: setting the initial state; determining the specific number of model runs corresponding to the time horizon of calculations; making final calculations and visually presenting simulation outcomes. The author proposes one of the possible methods to formalise behaviour rules of heterogeneous agents that includes the choice of the digitalisation strategy and operational decision-making. The results of the study can offer support for the practical implementation of the simulation model within a specific computer environment and lay the foundations for the control system of a region’s industry digitalisation.


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