Spatial interactions in agent-based modeling

Agent Based Modeling (ABM) has become a widespread approach to model complex interactions. In this chapter after briefly summarizing some features of ABM the different approaches in modeling spatial interactions are discussed. It is stressed that agents can interact either indirectly through a shared environment and/or directly with each other. In such an approach, higher-order variables such as commodity prices, population dynamics or even institutions, are not exogenously specified but instead are seen as the results of interactions. It is highlighted in the chapter that the understanding of patterns emerging from such spatial interaction between agents is a key problem as much as their description through analytical or simulation means. The chapter reviews different approaches for modeling agents' behavior, taking into account either explicit spatial (lattice based) structures or networks. Some emphasis is placed on recent ABM as applied to the description of the dynamics of the geographical distribution of economic activities, - out of equilibrium. The Eurace@Unibi Model, an agent-based macroeconomic model with spatial structure, is used to illustrate the potential of such an approach for spatial policy analysis.Comment: 26 pages, 5 figures, 105 references; a chapter prepared for the book "Complexity and Geographical Economics - Topics and Tools", P. Commendatore, S.S. Kayam and I. Kubin, Eds. (Springer, in press, 2014

A lexicographical dynamic flow model for relief operations

Emergency management is a highly relevant area of interest in operations research. Currently the area is undergoing widespread development. Furthermore, recent disasters have highlighted the importance of disaster management, in order to alleviate the suffering of vulnerable people and save lives. In this context, the problem of designing plans for the distribution of humanitarian aid according to the preferences of the decision maker is crucial. In this paper, a lexicographical dynamic flow model to solve this problem is presented, extending a previously introduced static flow model. The new model is validated in a realistic case study and a computational study is performed to compare both models, showing how they can be coordinated to improve their overall performance

Emergency logistics for wildfire suppression based on forecasted disaster evolution

This paper aims to develop a two-layer emergency logistics system with a single depot and multiple demand sites for wildfire suppression and disaster relief. For the first layer, a fire propagation model is first built using both the flame-igniting attributes of wildfires and the factors affecting wildfire propagation and patterns. Second, based on the forecasted propagation behavior, the emergency levels of fire sites in terms of demand on suppression resources are evaluated and prioritized. For the second layer, considering the prioritized fire sites, the corresponding resource allocation problem and vehicle routing problem (VRP) are investigated and addressed. The former is approached using a model that can minimize the total forest loss (from multiple sites) and suppression costs incurred accordingly. This model is constructed and solved using principles of calculus. To address the latter, a multi-objective VRP model is developed to minimize both the travel time and cost of the resource delivery vehicles. A heuristic algorithm is designed to provide the associated solutions of the VRP model. As a result, this paper provides useful insights into effective wildfire suppression by rationalizing resources regarding different fire propagation rates. The supporting models can also be generalized and tailored to tackle logistics resource optimization issues in dynamic operational environments, particularly those sharing the same feature of single supply and multiple demands in logistics planning and operations (e.g., allocation of ambulances and police forces). © 2017 The Author(s

Protein Transfection Study Using Multicellular Tumor Spheroids of Human Hepatoma Huh-7 Cells

Several protein transfection reagents are commercially available and are powerful tools for elucidating function of a protein in a cell. Here we described protein transfection studies of the commercially available reagents, Pro- DeliverIN, Xfect, and TuboFect, using Huh-7 multicellular tumor spheroid (MCTS) as a three-dimensional in vitro tumor model. A cellular uptake study using specific endocytosis inhibitors revealed that each reagent was internalized into Huh-7 MCTS by different mechanisms, which were the same as monolayer cultured Huh-7 cells. A certain amount of Pro-DeliverIN and Xfect was uptaken by Huh-7 cells through caveolae-mediated endocytosis, which may lead to transcytosis through the surface-first layered cells of MCTS. The results presented here will help in the choice and use of protein transfection reagents for evaluating anti-tumor therapeutic proteins against MCTS models

Decreasing the Economic Vulnerability of the Built Environment throughout the Disaster Recovery Processes: An Agent based Model Framework

The recurrent disastrous events impact a broad spectrum of stakeholders. Accordingly, decision-makers need to decrease the vulnerability of the built environment to future hazards to achieve long-term sustainability for the future generations. This paper discusses a decision-making framework via an agent-based model that assimilates the different participating entities in the recovery processes, while decreasing the economic vulnerability of the built environment. The developed model accounts for the objectives of the government agencies, and the needs of the residential and economic sectors in repairing their households and regaining the monthly revenue. The developed model utilizes a learning module that depicts the learning behavior of the stakeholders. In addition, the model utilizes a well-established economic vulnerability indicator that evaluates the susceptibility of the community to economic losses. Through integrating the economic vulnerability indicator into the associated stakeholder\u27s objective function, effective strategies for post-disaster recovery were identified. The model was tested on the post-Katrina recovery in the three coastal counties of Mississippi. The model was able to provide better recovery, and lower economic vulnerability values in comparison to the existing conditions in the three counties. As such, the proposed decision-making framework can be utilized by the recovery and planning agencies to balance between the short-term redevelopment objectives, and the long-term goals in decreasing the built environment vulnerabilities. Such innovative decision-making framework will be implemented on other case studies to furtherly validate the results of the model

Ontologies for crisis management: a review of state of the art in ontology design and usability

The growing use of a variety of information systems in crisis management both by non-governmental organizations (NGOs) and emergency management agencies makes the challenges of information sharing and interoperability increasingly important. The use of semantic web technologies is a growing area and is a technology stack specifically suited to these challenges. This paper presents a review of ontologies, vocabularies and taxonomies that are useful in crisis management systems. We identify the different subject areas relevant to crisis management based on a review of the literature. The different ontologies and vocabularies available are analysed in terms of their coverage, design and usability. We also consider the use cases for which they were designed and the degree to which they follow a variety of standards. While providing comprehensive ontologies for the crisis domain is not feasible or desirable there is considerable scope to develop ontologies for the subject areas not currently covered and for the purposes of interoperability